[edit]

AISTATS 2022 Accepted Papers

• Cross-Loss Influence Functions to Explain Deep Network Representations
  Silva, Andrew; Chopra, Rohit; Gombolay, Matthew


• Federated Reinforcement Learning with Environment Heterogeneity
  Jin, Hao; Peng, Yang; Yang, Wenhao; Wang, Shusen; Zhang, Zhihua


• On Linear Model with Markov Signal Priors
  Truong, Lan V


• Maillard Sampling: Boltzmann Exploration Done Optimally
  Bian, Jie; Jun, Kwang-Sung


• Norm-Agnostic Linear Bandits
  Gales, Spencer B; Sethuraman, Sunder; Jun, Kwang-Sung


• Gaussian Process Bandit Optimization with Few Batches
  Li, Zihan; Scarlett, Jonathan


• Approximate Function Evaluation via Multi-Armed Bandits
  Baharav, Tavor Z; Cheng, Gary; Pilanci, Mert; Tse, David


• Unlabeled Data Help: Minimax Analysis and Adversarial Robustness
  Xing, Yue; Song, Qifan; Cheng, Guang


• System-Agnostic Meta-Learning for MDP-based Dynamic Scheduling via Descriptive Policy
  Lee, Hyun-Suk


• Deep Layer-wise Networks Have Closed-Form Weights
  Wu, Chieh Tzu; Masoomi, Aria; Gretton, Arthur; Dy, Jennifer


• Sequential Multivariate Change Detection with Calibrated and Memoryless False Detection Rates
  Cobb, Oliver; Van Looveren, Arnaud; Klaise, Janis


• Neural Contextual Bandits without Regret
  Kassraie, Parnian; Krause, Andreas


• SAN: Stochastic Average Newton Algorithm for Minimizing Finite Sums
  CHEN, Jiabin; YUAN, Rui; Garrigos, Guillaume; Gower, Robert M


• Factorization Approach for Low-complexity Matrix Completion Problems: Exponential Number of Spurious Solutions and Failure of Gradient Methods
  Yalçın, Baturalp; Zhang, Haixiang; Lavaei, Javad; Sojoudi, Somayeh


• k-experts - Online Policies and Fundamental Limits
  Mukhopadhyay, Samrat; Sahoo, Sourav; Sinha, Abhishek


• Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity
  Gorbunov, Eduard; Loizou, Nicolas; Gidel, Gauthier


• Multi-armed Bandit Algorithm against Strategic Replication
  Shin, Suho; Lee, Seungjoon; Ok, Jungseul


• Gap-Dependent Bounds for Two-Player Markov Games
  Dou, Zehao; Yang, Zhuoran; Wang, Zhaoran; Du, Simon


• Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference Bandits
  Saha, Aadirupa; Ghoshal, Suprovat


• Exploring Image Regions Not Well Encoded by an INN
  Ling, Zenan; Zhou, Fan; Wei, Meng; Zhang, Quanshi


• Finding Dynamics Preserving Adversarial Winning Tickets
  Shi, Xupeng; Zheng, Pengfei; Ding, A. Adam; Gao, Yuan; Zhang, Weizhong


• Being a Bit Frequentist Improves Bayesian Neural Networks
  Kristiadi, Agustinus; Hein, Matthias; Hennig, Philipp


• Jointly Efficient and Optimal Algorithms for Logistic Bandits
  Faury, Louis; Abeille, Marc; Jun, Kwang-Sung; Calauzenes, Clement


• Obtaining Causal Information by Merging Datasets with MAXENT
  Garrido Mejia, Sergio H; Kirschbaum, Elke; Janzing, Dominik


• Distributed Sparse Multicategory Discriminant Analysis
  Chen, Hengchao; Sun, Qiang


• Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential Equations
  Krämer, Nicholas; Schmidt, Jonathan; Hennig, Philipp


• A View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy
  Bello, Kevin; Ke, Chuyang; Honorio, Jean


• Marginalized Operators for Off-policy Reinforcement Learning
  Tang, Yunhao; Rowland, Mark; Munos, Remi; Valko, Michal


• Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning
  Qian, Xun; Islamov, Rustem; Safaryan, Mher; Richtarik, Peter


• Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations
  Xu, Winnie; Chen, Ricky T. Q.; Li, Xuechen; Duvenaud, David


• Causally motivated shortcut removal using auxiliary labels
  Makar, Maggie; Packer, Ben; Moldovan, Dan; Blalock, Davis; Halpern, Yoni; D'Amour, Alexander


• Learning to Plan Variable Length Sequences of Actions with a Cascading Bandit Click Model of User Feedback
  Santara, Anirban; Aggarwal, Gaurav; Li, Shuai; Gentile, Claudio


• Identity Testing of Reversible Markov Chains
  Fried, Sela; Wolfer, Geoffrey


• Sampling in Dirichlet Process Mixture Models for Clustering Streaming Data
  Dinari, Or; Freifeld, Oren


• A Globally Convergent Evolutionary Strategy for Stochastic Constrained Optimization with Applications to Reinforcement Learning
  Diouane, Youssef; Lucchi, Aurelien; Patil, Vihang Prakash


• Adaptively Partitioning Max-Affine Estimators for Convex Regression
  Balázs, Gábor


• Variational Marginal Particle Filters
  Lai, Jinlin; Domke, Justin; Sheldon, Daniel


• On Structured Filtering-Clustering: Global Error Bound and Optimal First-Order Algorithms
  Ho, Nhat; Lin, Tianyi; Jordan, Michael


• Robustness and Reliability When Training With Noisy Labels
  Olmin, Amanda; Lindsten, Fredrik


• Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap
  Dellaporta, Charita; Knoblauch, Jeremias ; Damoulas, Theodoros; Briol, Francois-Xavier


• A Last Switch Dependent Analysis of Satiation and Seasonality in Bandits
  Laforgue, Pierre; Clerici, Giulia; Cesa-Bianchi, Nicolò; Gilad-Bachrach, Ran


• Analysis of a Target-Based Actor-Critic Algorithm with Linear Function Approximation
  BARAKAT, Anas; Bianchi, Pascal; Lehmann, Julien


• Policy Learning and Evaluation with Randomized Quasi-Monte Carlo
  Arnold, Sébastien M. R.; L'Ecuyer, Pierre; Chen, Liyu; Chen, Yi-fan; Sha, Fei


• Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback
  Hoang, Nghia; Deoras, Anoop; Zhao, Tong; Li, Jin; Karypis, George


• Multiway Spherical Clustering via Degree-Corrected Tensor Block Models
  Hu, Jiaxin; Wang, Miaoyan


• Fixed Support Tree-Sliced Wasserstein Barycenter
  Takezawa, Yuki; Sato, Ryoma; Kozareva, Zornitsa; Ravi, Sujith; Yamada, Makoto


• k-Pareto Optimality-Based Sorting with Maximization of Choice
  Ruppert, Jean; Aleksandrova, Marharyta; Engel, Thomas


• Towards Return Parity in Markov Decision Processes
  Chi, Jianfeng; Shen, Jian; Dai, Xinyi; Zhang, Weinan; Tian, Yuan; Zhao, Han


• Uncertainty Quantification for Low-Rank Matrix Completion with Heterogeneous and Sub-Exponential Noise
  Farias, Vivek; Li, Andrew A; Peng, Tianyi


• Survival regression with proper scoring rules and monotonic neural networks
  Rindt, David; Hu, Robert; Steinsaltz, David; Sejdinovic, Dino


• Physics Informed Deep Kernel Learning
  Wang, Zheng; Xing, Wei; Kirby, Robert; Zhe, Shandian


• Fast Distributionally Robust Learning with Variance-Reduced Min-Max Optimization
  Yu, Yaodong; Lin, Tianyi; Mazumdar, Eric V; Jordan, Michael


• Heavy-tailed Streaming Statistical Estimation
  Tsai, Che-Ping; Prasad, Adarsh; Balakrishnan, Sivaraman; Ravikumar, Pradeep


• On Distributionally Robust Optimization and Data Rebalancing
  Słowik, Agnieszka; Bottou, Leon


• Spiked Covariance Estimation from Modulo-Reduced Measurements
  Romanov, Elad; Ordentlich, Or


• A Contraction Theory Approach to Optimization Algorithms from Acceleration Flows
  Cisneros-Velarde, Pedro; Bullo, Francesco


• Robust Probabilistic Time Series Forecasting
  Yoon, TaeHo; Park, Youngsuk; Ryu, Ernest K; Wang, Yuyang


• VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition
  Ardywibowo, Randy; Boluki, Shahin; Wang, Zhangyang; Mortazavi, Bobak J; Huang, Shuai; Qian, Xiaoning


• Implicitly Regularized RL with Implicit Q-values
  Vieillard, Nino; Andrychowicz, Marcin; Raichuk, Anton; Pietquin, Olivier; Geist, Matthieu


• A Witness Two-Sample Test
  Kübler, Jonas M; Jitkrittum, Wittawat; Schölkopf, Bernhard; Muandet, Krikamol


• Sample-and-threshold differential privacy: Histograms and applications
  Cormode, Graham; Bharadwaj, Akash


• Common Failure Modes of Subcluster-based Sampling in Dirichlet Process Gaussian Mixture Models - and a Deep-learning Solution
  Winter, Vlad; Dinari, Or; Freifeld, Oren


• A Complete Characterisation of ReLU-Invariant Distributions
  Macdonald, Jan; Wäldchen, Stephan


• Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations
  Yeh, Chih-Kuan ; Lee, Kuan-Yun; Liu, Frederick; Ravikumar, Pradeep


• Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference
  Rendsburg, Luca; Kristiadi, Agustinus; Hennig, Philipp; von Luxburg, Ulrike


• Equivariance Discovery by Learned Parameter-Sharing
  Yeh, Raymond A; Hu, Yuan-Ting; Hasegawa-Johnson, Mark; Schwing, Alexander


• Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits
  Tao, Youming; Wu, Yulian; Zhao, Peng; Wang, Di


• Standardisation-function Kernel Stein Discrepancy: A Unifying View on Kernel Stein Discrepancy Tests for Goodness-of-fit
  Xu, Wenkai


• Parametric Bootstrap for Differentially Private Confidence Intervals
  Ferrando, Cecilia; Wang, Shufan; Sheldon, Daniel


• Nearly Tight Convergence Bounds for Semi-discrete Entropic Optimal Transport
  Delalande, Alex


• Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection
  Challu, Cristian I; Jiang, Peihong; Wu, Ying Nian; Callot, Laurent


• Online Page Migration with ML Advice
  Indyk, Piotr; Mallmann-Trenn, Frederik; Mitrovic, Slobodan; Rubinfeld, Ronitt


• Policy Learning for Optimal Individualized Dose Intervals
  Chen, Guanhua; li, xiaomao; Yu, Menggang


• Deep Multi-Fidelity Active Learning of High-Dimensional Outputs
  Li, Shibo; Wang, Zheng; Kirby, Robert; Zhe, Shandian


• Online Learning for Unknown Partially Observable MDPs
  Jafarnia Jahromi, Mehdi; Jain, Rahul; Nayyar, Ashutosh


• Is Bayesian Model-Agnostic Meta Learning Better than Model-Agnostic Meta Learning, Provably?
  Chen, Lisha; Chen, Tianyi


• A Bayesian Model for Online Activity Sample Sizes
  Richardson, Thomas S. ; Liu, Yu; McQueen, James; Hains, Doug


• Parallel MCMC Without Embarrassing Failures
  de Souza, Daniel A; Mesquita, Diego; Kaski, Samuel; Acerbi, Luigi


• Optimal Dynamic Regret in Proper Online Learning with Strongly Convex Losses and Beyond
  Baby, Dheeraj; Wang, Yu-Xiang


• Counterfactual Explanation Trees: Transparent and Consistent Actionable Recourse with Decision Trees
  Kanamori, Kentaro; Takagi, Takuya; Kobayashi, Ken; Ike, Yuichi


• Spectral risk-based learning using unbounded losses
  Holland, Matthew J; Haress, El Mehdi


• A Dual Approach to Constrained Markov Decision Processes with Entropy Regularization
  Ying, Donghao; Ding, Yuhao; Lavaei, Javad


• On the Global Optimum Convergence of Momentum-based Policy Gradient
  Ding, Yuhao; Zhang, Junzi; Lavaei, Javad


• Feature screening with kernel knockoffs
  Poignard, Benjamin; Naylor, Peter J; Climente-González, Héctor; Yamada, Makoto


• Bias-Variance Decompositions for Margin Losses
  Wood, Danny; Mu, Tingting; Brown, Gavin


• Grassmann Stein Variational Gradient Descent
  Liu, Xing; Zhu, Harrison; Ton, Jean-Francois; Wynne, George; Duncan, Andrew


• Nonstochastic Bandits and Experts with Arm-Dependent Delays
  van der Hoeven, Dirk; Cesa-Bianchi, Nicolò


• Improved analysis of randomized SVD for top-eigenvector approximation
  Tzeng, Ruo-Chun; Wang, Po-An; Adriaens, Florian; Gionis, Aristides; Lu, Chi-Jen


• p-Generalized Probit Regression and Scalable Maximum Likelihood Estimation via Sketching and Coresets
  Munteanu, Alexander; Omlor, Simon; Peters, Christian


• Non-stationary Online Learning with Memory and Non-stochastic Control
  Zhao, Peng; Wang, Yu-Xiang; Zhou, Zhi-Hua


• Dimensionality Reduction and Prioritized Exploration for Policy Search
  Memmel, Marius; Liu, Puze; Tateo, Davide; Peters, Jan


• The Curse Revisited: When are Distances Informative for the Ground Truth in Noisy High-Dimensional Data?
  Vandaele, Robin; Kang, Bo; De Bie, Tijl; Saeys, Yvan


• Improving Attribution Methods by Learning Submodular Functions
  Manupriya, Piyushi; Menta, Tarun Ram; Jagarlapudi, SakethaNath N; N Balasubramanian, Vineeth


• Conditional Gradients for the Approximately Vanishing Ideal
  Wirth, Elias S; Pokutta, Sebastian


• Efficient Algorithms for Extreme Bandits
  Baudry, Dorian; Russac, Yoan; Kaufmann, Emilie


• Rejection sampling from shape-constrained distributions in sublinear time
  Chewi, Sinho; Gerber, Patrik R; Lu, Chen; Le Gouic, Thibaut; Rigollet, Philippe


• Learning Inconsistent Preferences with Gaussian Processes
  Chau, Siu Lun; Gonzalez, Javier; Sejdinovic, Dino


• Bayesian Classifier Fusion with an Explicit Model of Correlation
  Trick, Susanne; Rothkopf, Constantin


• Conditionally Gaussian PAC-Bayes
  Clerico, Eugenio; Deligiannidis, George; Doucet, Arnaud


• Leveraging Time Irreversibility with Order-Contrastive Pre-training
  Agrawal, Monica N; Lang, Hunter; Offin, Michael; Gazit, Lior; Sontag, David


• Moment Matching Deep Contrastive Latent Variable Models
  Weinberger, Ethan; Beebe-Wang, Nicasia; Lee, Su-In


• Unifying Importance Based Regularisation Methods for Continual Learning
  Benzing, Frederik


• Differentially Private Histograms under Continual Observation: Streaming Selection into the Unknown
  Rivera Cardoso, Adrian; Rogers, Ryan


• Confident Least Square Value Iteration with Local Access to a Simulator
  Hao, Botao; Lazic, Nevena; Yin, Dong; Abbasi-Yadkori, Yasin; Szepesvari, Csaba


• Safe Optimal Design with Applications in Off-Policy Learning
  Zhu, Ruihao; Kveton, Branislav


• Accurate Shapley Values for explaining tree-based models
  I. Amoukou, Salim; Salaün, Tangi; Brunel, Nicolas


• A Single-Timescale Method for Stochastic Bilevel Optimization
  Chen, Tianyi; Sun, Yuejiao; Xiao, Quan; Yin, Wotao


• Strategic ranking
  Liu, Lydia T.; Garg, Nikhil; Borgs, Christian


• Encrypted Linear Contextual Bandit
  Garcelon, Evrard; Pirotta, Matteo; Perchet, Vianney


• Density Ratio Estimation via Infinitesimal Classification
  Choi, Kristy; Meng, Chenlin; Song, Yang; Ermon, Stefano


• AdaBlock: SGD with Practical Block Diagonal Matrix Adaptation for Deep Learning
  Yun, Jihun; Lozano, Aurelie; Yang, Eunho


• Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Completion
  Tong, Tian; Ma, Cong; Prater-Bennette, Ashley; Tripp, Erin; Chi, Yuejie


• Pairwise Supervision Can Provably Elicit a Decision Boundary
  Bao, Han; Shimada, Takuya; Xu, Liyuan; Sato, Issei; Sugiyama, Masashi


• An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization
  Rosenfeld, Elan; Ravikumar, Pradeep; Risteski, Andrej


• On the Convergence Rate of Off-Policy Policy Optimization Methods with Density-Ratio Correction
  Huang, Jiawei; Jiang, Nan


• Loss as the Inconsistency of a Probabilistic Dependency Graph: Choose Your Model, Not Your Loss Function
  Richardson, Oliver E


• Provably Efficient Policy Optimization for Two-Player Zero-Sum Markov Games
  Zhao, Yulai; Tian, Yuandong; Lee, Jason; Du, Simon


• One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation
  Ono, Hajime; Minami, Kazuhiro; Hino, Hideitsu


• Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably
  Liu, Tianyi; Li, Yan; Zhou, Enlu; Zhao, Tuo


• Robust Deep Learning from Crowds with Belief Propagation
  Kim, Hoyoung; Cho, Seunghyuk; Kim, Dongwoo; Ok, Jungseul


• Sampling from Arbitrary Functions via PSD Models
  Marteau-Ferey, Ulysse; Bach, Francis; Rudi, Alessandro


• Uncertainty Quantification for Bayesian Optimization
  Tuo, Rui; Wang, Wenjia


• Metalearning Linear Bandits by Prior Update
  Peleg, Amit; Pearl, Naama; Meir, Ron


• Fast Rank-1 NMF for Missing Data with KL Divergence
  Ghalamkari, Kazu; Sugiyama, Mahito


• Randomized Stochastic Gradient Descent Ascent
  Sebbouh, Othmane; Cuturi, marco; Peyré, Gabriel


• Aligned Multi-Task Gaussian Process
  Mikheeva, Olga; Kazlauskaite, Ieva; Hartshorne, Adam; Kjellström, Hedvig; Ek, Carl Henrik; Campbell, Neill


• Generative Models as Distributions of Functions
  Dupont, Emilien; Teh, Yee Whye; Doucet, Arnaud


• ContextGen: Targeted Data Generation for Low Resource Domain Specific Text Classification
  Fromme, Lukas; Bogojeska, Jasmina; Kuhn , Jonas


• Super-Acceleration with Cyclical Step-sizes
  Goujaud, Baptiste; Scieur, Damien; Dieuleveut, Aymeric; Taylor, Adrien B; Pedregosa, Fabian


• On PAC-Bayesian reconstruction guarantees for VAEs
  Chérief-Abdellatif, Badr-Eddine; Shi, Yuyang; Doucet, Arnaud; Guedj, Benjamin


• MT3: Meta Test-Time Training for Self-Supervised Test-Time Adaption
  Bartler, Alexander; Bühler, Andre; Wiewel, Felix; Döbler, Mario; Yang, Bin


• Random Effect Bandits
  Zhu, Rong; Kveton, Branislav


• DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor Search
  Karppa, Matti; Aumüller, Martin; Pagh, Rasmus


• Embedded Ensembles: infinite width limit and operating regimes
  Velikanov, Maksim; Kail, Roman V; Anokhin, Ivan; Vashurin, Roman; Panov, Maxim; Zaytsev, Alexey; Yarotsky, Dmitry


• State Dependent Performative Prediction with Stochastic Approximation
  LI, Qiang; Wai, Hoi-To


• Reward-Free Policy Space Compression for Reinforcement Learning
  Mutti, Mirco; Del Col, Stefano; Restelli, Marcello


• Nonstationary multi-output Gaussian processes via harmonizable spectral mixtures
  Altamirano, Matias; Tobar, Felipe


• Learning Quantile Functions for Temporal Point Processes with Recurrent Neural Splines
  BEN TAIEB, Souhaib


• Differentially Private Regression with Unbounded Covariates
  Milionis, Jason; Kalavasis, Alkis; Fotakis, Dimitris; Ioannidis, Stratis


• Triple-Q: A Model-Free Algorithm for Constrained Reinforcement Learning with Sublinear Regret and Zero Constraint Violation
  Wei, Honghao; Liu, Xin; Ying, Lei


• Measuring the robustness of Gaussian processes to kernel choice
  Stephenson, William T; Ghosh, Soumya; Nguyen, Tin D; Yurochkin, Mikhail; Deshpande, Sameer; Broderick, Tamara


• A general sample complexity analysis of vanilla policy gradient
  YUAN, Rui; Gower, Robert M; Lazaric, Alessandro


• Pairwise Fairness for Ordinal Regression
  Kleindessner, Matthäus; Samadi, Samira; Zafar, Muhammad Bilal; Kenthapadi, Krishnaram; Russell, Chris


• LIMESegment: Meaningful, Realistic Time Series Explanations
  Sivill, Torty; Flach, Peter


• A Random Matrix Perspective on Mixtures of Nonlinearities in High Dimensions
  Adlam, Ben; Levinson, Jake A; Pennington, Jeffrey


• Spectral Pruning for Recurrent Neural Networks
  Furuya, Takashi; Suetake, Kazuma; Taniguchi, Koichi; Kusumoto, Hiroyuki; Saiin, Ryuji ; Daimon, Tomohiro


• Many processors, little time: MCMC for partitions via optimal transport couplings
  Nguyen, Tin D; Trippe, Brian L; Broderick, Tamara


• Sinkformers: Transformers with Doubly Stochastic Attention
  Sander, Michael E.; Ablin, Pierre; Blondel, Mathieu; Peyré, Gabriel


• Finding Nearly Everything within Random Binary Networks
  Sreenivasan, Kartik; Rajput, Shashank; Sohn, Jy-yong; Papailiopoulos, Dimitris


• Last Layer Marginal Likelihood for Invariance Learning
  Schwöbel, Pola; Jørgensen, Martin; Ober, Sebastian W; van der Wilk, Mark


• Minimax Optimization: The Case of Convex-Submodular
  Adibi, Arman; Mokhtari, Aryan; Hassani, Hamed


• Federated Learning with Buffered Asynchronous Aggregation
  Nguyen, John; Malik, Kshitiz; Zhan, Hongyuan; Yousefpour, Ashkan; Rabbat, Mike; Malek, Mani; Huba, Dzmitry


• Bayesian Inference and Partial Identification in Multi-Treatment Causal Inference with Unobserved Confounding
  Zheng, Jiajing; D'Amour, Alexander; Franks, Alexander


• Deep Neyman-Scott Processes
  Hong, Chengkuan; Shelton, Christian


• CATVI: Conditional and Adaptively Truncated Variational Inference for Hierarchical Bayesian Nonparametric Models
  Liu, Yirui; Qiao, Xinghao; Lam, Jessica


• Certifiably Robust Variational Autoencoders
  Barrett, Ben; Camuto, Alexander; Willetts, Matthew; Rainforth, Tom


• Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums
  Zhou, Kaiwen; Tian, Lai; So, Anthony Man-Cho; Cheng, James


• On Margins and Derandomisation in PAC-Bayes
  Biggs, Felix; Guedj, Benjamin


• A Spectral Perspective of DNN Robustness to Label Noise
  Bar, Oshrat; Drory, Amnon; Giryes, Raja


• Momentum Accelerates the Convergence of Stochastic AUPRC Maximization
  Wang, Guanghui ; YANG, MING; Zhang, Lijun; Yang, Tianbao


• Computing D-Stationary Points of $\rho$-Margin Loss SVM
  Tian, Lai; So, Anthony Man-Cho


• A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality
  Zhang, Xuhui; Blanchet, Jose; Ghosh, Soumyadip; Squillante, Mark S


• An Information-Theoretic Justification for Model Pruning
  Isik, Berivan; Weissman, Tsachy; No, Albert


• Flexible Accuracy for Differential Privacy
  Bansal, Aman; Chunduru, Rahul; Data, Deepesh; Prabhakaran, Manoj


• Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation
  Wu, Yue; Zhou, Dongruo; Gu, Quanquan


• On Facility Location Problem in the Local Differential Privacy Model
  Cohen-Addad, Vincent; Esencayi, Yunus; Fan, Chenglin; Gaboradi, Marco; Li, Shi; Wang, Di


• Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent
  Ren, Tongzheng; Cui, Fuheng; Atsidakou, Alexia; Sanghavi, Sujay; Ho, Nhat


• MLDemon:Deployment Monitoring for Machine Learning Systems
  Ginart, Tony; Zhang, Martin Jinye; Zou, James


• How to Learn when Data Gradually Reacts to Your Model
  Izzo, Zachary; Zou, James; Ying, Lexing


• Mitigating Bias in Calibration Error Estimation
  Roelofs, Rebecca; Cain, Nicholas; Shlens, Jonathon; Mozer, Michael C


• Privacy Amplification by Subsampling in Time Domain
  Koga, Tatsuki; Meehan, Casey ; Chaudhuri, Kamalika


• How and When Random Feedback Works: A Case Study of Low-Rank Matrix Factorization
  Garg, Shivam; Vempala, Santosh


• Gap-Dependent Unsupervised Exploration for Reinforcement Learning
  Wu, Jingfeng; Braverman, Vladimir; Yang, Lin


• On the Generalization of Representations in Reinforcement Learning
  Le Lan, Charline; Tu, Stephen; Oberman, Adam; Agarwal, Rishabh; G. Bellemare, Marc


• Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects
  Zhang, Yao; Berrevoets, Jeroen; van der Schaar, Mihaela


• Learning a Single Neuron for Non-monotonic Activation Functions
  Wu, Lei


• Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis
  Teng, Jiaye; Huang, Weiran; He, Haowei


• Model-free Policy Learning with Reward Gradients
  Lan, Qingfeng; Tosatto, Samuele; Farrahi, Homayoon; Mahmood, Rupam


• Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes
  Lin, Zhiyuan Jerry; Astudillo, Raul; Frazier, Peter; Bakshy, Eytan


• Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPs
  He, Jiafan; Zhou, Dongruo; Gu, Quanquan


• Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization
  Thekumparampil, Kiran K; He, Niao; Oh, Sewoong


• Denoising and change point localisation in piecewise-constant high-dimensional regression coefficients
  Wang, Fan; Madrid, Oscar; Yu, Yi; Rinaldo, Alessandro


• Optimal partition recovery in general graphs
  Yu, Yi; Madrid, Oscar; Rinaldo, Alessandro


• On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization
  Kim, Jungtaek; Choi, Seungjin


• Offline Policy Selection under Uncertainty
  Yang, Mengjiao; Dai, Bo; Nachum, Ofir; Tucker, George; Schuurmans, Dale


• On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity
  Le, Khang; Nguyen, Huy; Nguyen, Khai; Pham, Tung; Ho, Nhat


• Independent Natural Policy Gradient always converges in Markov Potential Games
  Fox, Roy; McAleer, Stephen M; Overman, Will; Panageas, Ioannis


• Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness
  Kim, Beomsu; Seo, Junghoon


• Projection Predictive Inference for Generalized Linear and Additive Multilevel Models
  Catalina, Alejandro; Bürkner, Paul-Christian; Vehtari, Aki


• Point Cloud Generation with Continuous Conditioning
  Triess, Larissa T; Bühler, Andre; Peter, David; Flohr, Fabian B.; Zöllner, Marius


• An Optimal Algorithm for Strongly Convex Minimization under Affine Constraints
  Salim, Adil; CONDAT, Laurent; Kovalev, Dmitry; Richtarik, Peter


• CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
  Lucic, Ana; ter Hoeve, Maartje A; Tolomei, Gabriele; de Rijke, Maarten; Silvestri, Fabrizio


• Safe Active Learning for Multi-Output Gaussian Processes
  Li, Cen-You; Rakitsch, Barbara; Zimmer, Christoph


• Variational Continual Proxy-Anchor for Deep Metric Learning
  Kim, Minyoung; Guerrero , Ricardo; Pham, Hai X; Pavlovic, Vladimir


• Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis
  Pawelczyk, Martin; Agarwal, Chirag; Joshi, Shalmali; Upadhyay, Sohini; Lakkaraju, Himabindu


• Variational Autoencoders: A Harmonic Perspective
  Camuto, Alexander; Willetts, Matthew


• On the Consistency of Max-Margin Losses
  Nowak, Alex; Rudi, Alessandro; Bach, Francis


• A prior-based approximate latent Riemannian metric
  Arvanitidis, Georgios; Georgiev, Bogdan M; Schölkopf, Bernhard


• On Convergence of Lookahead in Smooth Games
  Ha, Junsoo; Kim, Gunhee


• Learning Proposals for Practical Energy-Based Regression
  Gustafsson, Fredrik K; Danelljan, Martin; Schön, Thomas B.


• Predicting the impact of treatments over time with uncertainty aware neural differential equations.
  De Brouwer, Edward; Gonzalez, Javier; Hyland, Stephanie


• Improved Algorithms for Misspecified Linear Markov Decision Processes
  Vial, Daniel; Parulekar, Advait; Shakkottai, Sanjay; Srikant, R


• Synthsonic: Fast, Probabilistic modeling and Synthesis of Tabular Data
  Baak, Max; Brugman, Simon; Fridman Rojas, Ilan; Dalmeida, Lorraine; Urlus, Ralph E.Q.; Oger, Jean-Baptiste


• Lagrangian manifold Monte Carlo on Monge patches
  Hartmann, Marcelo; Girolami, Mark; Klami, Arto


• Optimal Accounting of Differential Privacy via Characteristic Function
  Zhu, Yuqing; Dong, Jinshuo; Wang, Yu-Xiang


• Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets
  Opolka, Felix; Zhi, Yin-Cong; Lió, Pietro; Dong, Xiaowen


• Bayesian Link Prediction with Deep Graph Convolutional Gaussian Processes
  Opolka, Felix; Lió, Pietro


• On the Interplay between Information Loss and Operation Loss in Representations for Classification
  Silva, Jorge; Tobar, Felipe


• Pulling back information geometry
  Arvanitidis, Georgios; González-Duque, Miguel; Pouplin, Alison; Kalatzis, Dimitrios; Hauberg, Soren


• Optimizing Early Warning Classifiers to Control False Alarms via a Minimum Precision Constraint
  Rath, Preetish; Hughes, Michael


• Resampling Base Distributions of Normalizing Flows
  Stimper, Vincent; Schölkopf, Bernhard; Hernandez-Lobato, Jose Miguel


• Federated Myopic Community Detection with One-shot Communication
  Ke, Chuyang; Honorio, Jean


• Variational Gaussian Processes: A Functional Analysis View
  Wynne, George; Wild , Veit


• Adversarially Robust Kernel Smoothing
  Zhu, Jia-Jie; Kouridi, Christina; Nemmour, Yassine; Schölkopf, Bernhard


• Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-Wolfe
  Sejourne, Thibault; Vialard, Francois-Xavier; Peyré, Gabriel


• Off-Policy Risk Assessment for Markov Decision Processes
  Huang, Audrey; Leqi, Liu; Lipton, Zachary ; Azizzadenesheli, Kamyar


• Predictive variational Bayesian inference as risk-seeking optimization
  Futami, Futoshi; Iwata, Tomoharu; Ueda, Naonori; Sato, Issei; Sugiyama, Masashi


• Kantorovich Mechanism for Pufferfish Privacy
  Ding, Ni


• Margin-distancing for safe model explanation
  Yan, Tom; Zhang, Chicheng


• Optimal transport with $f$-divergence regularization and generalized Sinkhorn algorithm
  Terjék, Dávid; González-Sánchez, Diego


• Modelling Non-Smooth Signals with Complex Spectral Structure
  Bruinsma, Wessel P; Tegnér, Martin; Turner, Richard E.


• Convergent Working Set Algorithm for Lasso with Non-Convex Sparse Regularizers
  Rakotomamonjy, Alain; Flamary, Rémi; Salmon, Joseph; Gasso, Gilles


• Particle-based Adversarial Local Distribution Regularization
  Nguyen-Duc, Thanh; Le, Trung; Zhao, He; Cai, Jianfei; Phung, Dinh


• Crowdsourcing Regression: A Spectral Approach
  Tenzer, Yaniv; Dror, Omer; Nadler, Boaz; Bilal, Erhan; Kluger, Yuval


• How to scale hyperparameters for quickshift image segmentation
  Garreau, Damien


• Wide Mean-Field Bayesian Neural Networks Ignore the Data
  Coker, Beau; Bruinsma, Wessel P; Burt, David R; Pan, Weiwei; Doshi-Velez, Finale


• Privacy Amplification by Decentralization
  Cyffers, Edwige; Bellet, Aurélien


• Reinforcement Learning with Fast Stabilization in Linear Dynamical Systems
  Lale, Sahin; Azizzadenesheli, Kamyar; Hassibi, Babak; Anandkumar, Animashree


• New Coresets for Projective Clustering and Applications
  Tukan, Murad; Wu, Xuan; Zhou, Samson; Braverman, Vladimir; Feldman, Dan


• Weak Separation in Mixture Models and Implications for Principal Stratification
  Ho, Nhat; Feller, Avi; Greif, Evan; Miratrix, Luke; Pillai, Natesh


• Using time-series privileged information for provably efficient learning of prediction models
  Karlsson, Rickard K.A.; Willbo, Martin; Hussain, Zeshan M; Krishnan, Rahul G.; Sontag, David; Johansson, Fredrik


• Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity
  Yang, Junchi; Orvieto, Antonio; Lucchi, Aurelien; He, Niao


• TD-GEN: Graph Generation Using Tree Decomposition
  Shirzad, Hamed; Hajimirsadeghi, Hossein; Abdi, Amir H.; Mori, Greg


• Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge
  Shah, Abhin; Shanmugam, Karthikeyan; Ahuja, Kartik


• SHAFF: Fast and consistent SHApley eFfect estimates via random Forests
  Bénard, Clément; Biau, Gérard; Da Veiga, Sébastien; Scornet, Erwan


• Almost Optimal Universal Lower Bound for Learning Causal DAGs with Atomic Interventions
  Porwal, Vibhor; Srivastava, Piyush; Sinha, Gaurav


• Estimators of Entropy and Information via Inference in Probabilistic Models
  Saad, Feras; Cusumano-Towner, Marco; Mansinghka, Vikash


• Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE
  Zhu, Yuqing; Wang, Yu-Xiang


• Fast and accurate optimization on the orthogonal manifold without retraction
  Ablin, Pierre; Peyré, Gabriel


• Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms
  Laroche, Romain; Tachet des Combes, Remi


• Efficient Kernelized UCB for Contextual Bandits
  Zenati, Houssam; Bietti, Alberto; Diemert, Eustache; Mairal, Julien; Martin, Matthieu; Gaillard, Pierre


• Acceleration in Distributed Optimization under Similarity
  Tian, Ye; Scutari, Gesualdo; Cao, Tianyu; Gasnikov, Alexander


• Corruption-robust Offline Reinforcement Learning
  Zhang, Xuezhou; Chen, Yiding; Zhu, Xiaojin; Sun, Wen


• A Cramér Distance perspective on Quantile Regression based Distributional Reinforcement Learning
  LHERITIER, Alix; Bondoux, Nicolas


• Orbital MCMC
  Neklyudov, Kirill; Welling, Max


• PAC Mode Estimation using PPR Martingale Confidence Sequences
  Jain , Shubham Anand; Shah, Rohan; Gupta, Sanit; Mehta, Denil; Nair, Inderjeet J; Vora, Jian; Khyalia, Sushil; Das, Sourav; Ribeiro, Vinay J; Kalyanakrishnan, Shivaram


• Harmless interpolation in regression and classification with structured features
  McRae, Andrew D; Karnik, Santhosh; Davenport, Mark; Muthukumar, Vidya K


• Masked Training of Neural Networks with Partial Gradients
  Mohtashami, Amirkeivan; Jaggi, Martin; Stich, Sebastian


• Learning in Stochastic Monotone Games with Decision-Dependent Data
  Narang, Adhyyan; Faulkner, Evan; Drusvyatskiy, Dmitriy; Fazel, Maryam; Ratliff, Lillian


• On Combining Bags to Better Learn from Label Proportions
  Saket, Rishi; Raghuveer, Aravindan; Ravindran, Balaraman


• Meta Learning MDPs with linear transition models
  Müller, Robert ; Pacchiano, Aldo


• Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals
  Brofos, James; Gabrie, Marylou; Brubaker, Marcus A; Lederman, Roy R


• Permutation Equivariant Layers for Higher Order Interactions
  Pan, Horace; Kondor, Risi


• Efficient Online Bayesian Inference for Neural Bandits
  Duran-Martin, Gerardo; Kara, Aleyna; Murphy, Kevin


• Parameter-Free Online Linear Optimization with Side Information via Universal Coin Betting
  Ryu, Jongha J; Bhatt, Alankrita; Kim, Young-Han


• Performative Prediction in a Stateful World
  Brown, Gavin; Hod, Shlomi; Kalemaj, Iden


• Learning Revenue-Maximizing Auctions With Differentiable Matching
  Curry, Michael J; Lyi, Uro; Goldstein, Tom; Dickerson, John P


• Orthogonal Multi-Manifold Enriching of Directed Networks
  Sawhney, Ramit; Agarwal, Shivam; Neerkaje, Atula T; Pathak, Kapil Jayesh


• Estimating Functionals of the Out-of-Sample Error Distribution in High-Dimensional Ridge Regression
  Patil, Pratik; Rinaldo, Alessandro; Tibshirani, Ryan


• The Tree Loss: Improving Generalization with Many Classes
  Wang, Yujie; Izbicki, Mike


• Double Control Variates for Gradient Estimation in Discrete Latent Variable Models
  Titsias, Michalis; Shi, Jiaxin


• Transfer Learning with Gaussian Processes for Bayesian Optimization
  Tighineanu, Petru; Skubch, Kathrin; Baireuther, Paul; Reiss, Attila; Berkenkamp, Felix; Vinogradska, Julia


• Conditional Linear Regression for Heterogeneous Covariances
  Liang, Leda; Juba, Brendan


• Learning Competitive Equilibria in Exchange Economies with Bandit Feedback
  Guo, Wenshuo; Kandasamy, Kirthevasan; Gonzalez, Joseph; Jordan, Michael; Stoica, Ion


• Node Feature Kernels Increase Graph Convolutional Network Robustness
  Seddik, Mohamed El Amine; Wu, Changmin; Lutzeyer, Johannes F.; Vazirgiannis, Michalis


• Top K Ranking for Multi-Armed Bandit with Noisy Evaluations
  Garcelon, Evrard; Avadhanula, Vashist; Lazaric, Alessandro; Pirotta, Matteo


• Differential privacy for symmetric log-concave mechanisms
  Vinterbo, Staal A


• Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization
  Wang, Yujia; Lin, Lu; Chen, Jinghui


• Fair Disaster Containment via Graph-Cut Problems
  Dinitz, Michael; Srinivasan, Aravind; Tsepenekas, Leonidas; Vullikanti, Anil


• Provable Lifelong Learning of Representations
  Cao, Xinyuan; Liu, Weiyang; Vempala, Santosh


• Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits
  Guo, Wenshuo; Agrawal, Kumar Krishna; Grover, Aditya; Muthukumar, Vidya K; Pananjady, Ashwin


• A New Notion of Individually Fair Clustering: $\alpha$-Equitable $k$-Center
  Chakrabarti, Darshan; Dickerson, John P; Esmaeili, Seyed A; Srinivasan, Aravind; Tsepenekas, Leonidas


• Iterative Alignment Flows
  Zhou, Zeyu; Gong, Ziyu; Ravikumar, Pradeep; Inouye, David I


• Fast Fourier Transform Reductions for Bayesian Network Inference
  Hsiao, Vincent; Nau, Dana; Dechter, Rina


• QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning
  Vono, Maxime; Plassier, Vincent; Durmus, Alain; Dieuleveut, Aymeric; Moulines, Eric


• Lifted Division for Lifted Hugin Belief Propagation
  Hoffmann, Moritz P; Braun, Tanya; Möller, Ralf


• Proximal Optimal Transport Modeling of Population Dynamics
  Bunne, Charlotte; Papaxanthos, Laetitia; Krause, Andreas; Cuturi, Marco


• Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits
  Li, Chuanhao; Wang, Hongning


• Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression
  Meanti, Giacomo; Carratino, Luigi; De Vito, Ernesto; Rosasco, Lorenzo


• Are All Linear Regions Created Equal?
  Gamba, Matteo; Chmielewski-Anders, Adrian; Sullivan, Josephine; Azizpour, Hossein; Bjorkman, Marten


• Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms
  Agterberg, Joshua; Sulam, Jeremias


• An Alternate Policy Gradient Estimator for Softmax Policies
  Garg, Shivam; Tosatto, Samuele; Pan, Yangchen; White, Martha; Mahmood, Rupam


• Co-Regularized Adversarial Learning for Multi-Domain Text Classification
  Wu, Yuan; Inkpen, Diana; El-Roby, Ahmed


• Zeroth-Order Methods for Convex-Concave Min-max Problems: Applications to Decision-Dependent Risk Minimization
  Maheshwari, Chinmay; Chiu, Chih-Yuan; Mazumdar, Eric; Sastry, Shankar; Ratliff, Lillian


• Near Instance Optimal Model Selection for Pure Exploration Linear Bandits
  Zhu, Yinglun; Katz-Samuels, Julian; Nowak, Robert


• Identification in Tree-shaped Linear Structural Causal Models
  van der Zander, Benito; Wienöbst, Marcel; Bläser, Markus; Liskiewicz, Maciej


• Pareto Optimal Model Selection in Linear Bandits
  Zhu, Yinglun; Nowak, Robert


• PAC Top-$k$ Identification under SST in Limited Rounds
  Agarwal, Arpit; Khanna, Sanjeev; Patil, Prathamesh


• Local SGD Optimizes Overparameterized Neural Networks in Polynomial Time
  Deng, Yuyang; Kamani, Mohammad Mahdi; Mahdavi, Mehrdad


• Dual-Level Adaptive Information Filtering for Interactive Image Segmentation
  Zheng, Ervine; Yu, Qi; Li, Rui; Shi, Pengcheng; Haake, Anne


• On the Value of Prior in Online Learning to Rank
  Kveton, Branislav; Meshi, Ofer; Zoghi, Masrour; Qin, Zhen


• Doubly Mixed-Effects Gaussian Process Regression
  Yoon, Jun Ho; Jeong, Daniel P; Kim, Seyoung


• Weighted Gaussian Process Bandits for Non-stationary Environments
  Deng, Yuntian; Zhou, Xingyu; Kim, Baekjin; Tewari, Ambuj; Gupta, Abhishek; Shroff, Ness


• Conditionally Tractable Density Estimation using Neural Networks
  Dong, Hailiang; Roy, Chiradeep; Rahman, Tahrima; Gogate, Vibhav; Ruozzi, Nicholas


• Common Information based Approximate State Representations in Multi-Agent Reinforcement Learning
  Kao, Hsu; Subramanian, Vijay


• Sensing Cox Processes via Posterior Sampling and Positive Bases
  Mutny, Mojmir; Krause, Andreas


• A Predictive Approach to Bayesian Nonparametric Survival Analysis
  Fong, Edwin; Lehmann, Brieuc


• On the equivalence of Oja's algorithm and GROUSE
  Balzano, Laura


• Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes
  Nava, Elvis; Mutny, Mojmir; Krause, Andreas


• Label differential privacy via clustering
  Esfandiari, Hossein; Mirrokni, Vahab; Syed, Umar; Vassilvitskii, Sergei


• Neural score matching for high-dimensional causal inference
  Clivio, Oscar; Falck, Fabian; Lehmann, Brieuc; Deligiannidis, George; Holmes, Chris


• Robust Stochastic Linear Contextual Bandits Under Adversarial Attacks
  DING, QIN; Hsieh, Cho-Jui; Sharpnack, James


• Multi-class classification in nonparametric active learning
  Ndjia Njike, Boris; Siebert, Xavier


• On the Assumptions of Synthetic Control Methods
  Shi, Claudia; Sridhar, Dhanya; Misra, Vishal; Blei, David


• Faster Rates, Adaptive Algorithms, and Finite-Time Bounds for Linear Composition Optimization and Gradient TD Learning
  Raj, Anant; Joulani, Pooria; Gyorgy, Andras; Szepesvari, Csaba


• Investigating the Role of Negatives in Contrastive Representation Learning
  Ash, Jordan; Goel, Surbhi; Krishnamurthy, Akshay; Misra, Dipendra


• Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference
  Ghassami, AmirEmad; Ying, Andrew; Shpitser, Ilya; Tchetgen Tchetgen, Eric


• Derivative-Based Neural Modelling of Cumulative Distribution Functions for Survival Analysis
  Danks, Dominic; Yau, Christopher


• Cycle Consistent Probability Divergences Across Different Spaces
  Zhang, Zhengxin ; Mroueh, Youssef; Goldfeld, Ziv; Sriperumbudur, Bharath


• Warping Layer: Representation Learning for Label Structures in Weakly Supervised Learning
  Ma, Yingyi; Zhang, Xinhua


• A Bandit Model for Human-Machine Decision Making with Private Information and Opacity
  Bordt, Sebastian; von Luxburg, Ulrike


• Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization
  Rando, Marco; Carratino, Luigi; Villa, Silvia; Rosasco, Lorenzo


• Adaptive Multi-Goal Exploration
  Tarbouriech, Jean; Darwiche Domingues, Omar; Menard, Pierre; Pirotta, Matteo; Valko, Michal; Lazaric, Alessandro


• Chernoff Sampling for Active Testing and Extension to Active Regression
  Mukherjee, Subhojyoti; Tripathy, Ardhendu S; Nowak, Robert


• An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift
  Aminian, Gholamali; Abroshan, Mahed; Khalili, Mohammad Mahdi; Toni, Laura; Rodrigues, Miguel


• Optimal Design of Stochastic DNA Synthesis Protocols based on Generative Sequence Models
  Weinstein, Eli N; Amin, Alan N; Grathwohl, Will S; Kassler, Daniel; Disset, Jean; Marks, Debora


• Approximate Top-$m$ Arm Identification with Heterogeneous Reward Variances
  Zhou, Ruida; Tian, Chao


• On perfectness in Gaussian graphical models
  Amini, Arash; Aragam, Bryon; Zhou, Qing


• GalilAI: Out-of-Task Distribution Detection using Causal Active Experimentation for Safe Transfer RL
  Sontakke, Sumedh A; Iota, Stephen; Hu, Zizhao; Mehrjou, Arash; Itti, Laurent; Schölkopf, Bernhard


• Efficient interventional distribution learning in the PAC framework
  Bhattacharyya, Arnab; Gayen, Sutanu; Kandasamy, Saravanan; Raval, Vedant; Variyam, Vinodchandran N.


• Dropout as a Regularizer of Interaction Effects
  Lengerich, Benjamin J; Xing, Eric; Caruana, Rich


• Thompson Sampling with a Mixture Prior
  Hong, Joey; Kveton, Branislav; Zaheer, Manzil; Ghavamzadeh, Mohammad; Boutilier, Craig


• SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification
  Panda, Ashwinee; Mahloujifar, Saeed; Bhagoji, Arjun Nitin; Chakraborty, Supriyo; Mittal, Prateek


• Nearly Optimal Algorithms for Level Set Estimation
  Mason, Blake; Jain, Lalit; Mukherjee, Subhojyoti; Camilleri, Romain; Jamieson, Kevin; Nowak, Robert


• Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization
  Zhang, Guodong; Wang, Yuanhao; Lessard, Laurent; Grosse, Roger B


• Optimal Compression of Locally Differentially Private Mechanisms
  Shah, Abhin; Chen, Wei-Ning; Ballé, Johannes; Kairouz, Peter; Theis, Lucas


• Hierarchical Bayesian Bandits
  Hong, Joey; Kveton, Branislav; Zaheer, Manzil; Ghavamzadeh, Mohammad


• Complex Momentum for Optimization in Games
  Lorraine, Jonathan P; Acuna, David ; Vicol, Paul; Duvenaud, David


• Asymptotically Optimal Locally Private Heavy Hitters via Parameterized Sketches
  Wu, Hao; Wirth, Anthony


• Tuning-Free Generalized Hamiltonian Monte Carlo
  Hoffman, Matthew D; Sountsov, Pavel


• Federated Functional Gradient Boosting
  Shen, Zebang; Hassani, Hamed; Kale, Satyen; Karbasi, Amin


• Generalised GPLVM with Stochastic Variational Inference
  Lalchand, Vidhi ; Ravuri, Aditya; Lawrence, Neil D


• Stochastic Extragradient: General Analysis and Improved Rates
  Gorbunov, Eduard; Berard, Hugo; Gidel, Gauthier; Loizou, Nicolas


• Deep Non-crossing Quantiles through the Partial Derivative
  Brando, Axel; Gimeno, Joan; Rodriguez-Serrano, Jose; Vitria, Jordi


• Optimal channel selection with discrete QCQP
  Jeong, Yeonwoo; Lee, Deokjae; An, Gaon; Son, Changyong; Song, Hyun Oh


• Vanishing Curvature in Randomly Initialized Deep ReLU Networks
  Orvieto, Antonio; Kohler, Jonas; Pavllo, Dario; Hofmann, Thomas; Lucchi, Aurelien


• Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes
  Dance, Hugh; Paige, Brooks


• Self-training Converts Weak Learners to Strong Learners in Mixture Models
  Frei, Spencer; Zou, Difan ; Chen, Zixiang; Gu, Quanquan


• Two-Sample Test with Kernel Projected Wasserstein Distance
  Wang, Jie; Gao, Rui; Xie, Yao


• Mode estimation on matrix manifolds: Convergence and robustness
  Sasaki, Hiroaki ; Hirayama, Jun-ichiro; Kanamori, Takafumi


• A Dimensionality Reduction Method for Finding Least Favorable Priors with a Focus on Bregman Divergence
  Dytso, Alex R; Goldenbaum, Mario; Poor, H. Vincent; Shamai, Shlomo


• Towards Federated Bayesian Network Structure Learning with Continuous Optimization
  Ng, Ignavier; Zhang, Kun


• Nuances in Margin Conditions Determine Gains in Active Learning
  Kpotufe, Samory; Yuan, Gan; ZHAO, YUNFAN


• Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting
  Park, Youngsuk; Maddix, Danielle; Aubet, François-Xavier; Kan, Kelvin; Gasthaus, Jan; Wang, Yuyang


• Convergence of Langevin Monte Carlo in Chi-Squared and Rényi Divergence
  Erdogdu, Murat A; Hosseinzadeh, Rasa; Zhang, Shunshi


• On the Convergence of Continuous Constrained Optimization for Structure Learning
  Ng, Ignavier; Lachapelle, Sebastien; Ke, Nan Rosemary; Lacoste-Julien, Simon; Zhang, Kun


• Hardness of Learning a Single Neuron with Adversarial Label Noise
  Diakonikolas, Ilias; Kane, Daniel; Manurangsi, Pasin; Ren, Lisheng


• Firebolt: Weak Supervision Under Weaker Assumptions
  Kuang, Zhaobin; Arachie, Chidubem G; Liang, Bangyong; Narayana, Pradyumna; DeSalvo, Giulia; Quinn, Michael S; Huang, Bert; Downs, Geoffrey; Yang, Yang


• Relational Neural Markov Random Fields
  Chen, Yuqiao; Natarajan, Sriraam; Ruozzi, Nicholas


• PACm-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime
  Morningstar, Warren R; Alemi, Alex; Dillon, Joshua V


• Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape
  Bisla, Devansh; Wang, Jing; Choromanska, Anna


• Online Control of the False Discovery Rate under “Decision Deadlines”
  Fisher, Aaron J


• Tile Networks: Learning Optimal Geometric Layout for Whole-page Recommendation
  Xiao, Shuai; Jiang, Zaifan; Yang, Shuang


• A Bayesian Approach for Stochastic Continuum-armed Bandit with Long-term Constraints
  Shi, Zai; Eryilmaz, Atilla


• Amortized Rejection Sampling in Universal Probabilistic Programming
  Naderiparizi, Saeid; Scibior, Adam; Munk, Andreas; Ghadiri, Mehrdad; Baydin, Atilim Gunes; Gram-Hansen, Bradley J; Schroeder de Witt, Christian A; Zinkov, Robert; Torr, Philip; Rainforth, Tom; Teh, Yee Whye; Wood, Frank


• The Curse of Passive Data Collection in Batch Reinforcement Learning
  Xiao, Chenjun; LEE, ILBIN; Dai, Bo; Schuurmans, Dale; Szepesvari, Csaba


• Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization
  Dresdner, Gideon; Vladarean, Maria-Luiza; Rätsch, Gunnar; Locatello, Francesco; Cevher, Volkan; Yurtsever, Alp


• Adversarial Tracking Control via Strongly Adaptive Online Learning with Memory
  Zhang, Zhiyu; Cutkosky, Ashok; Paschalidis, Ioannis


• Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation
  Letham, Benjamin; Guan , Phillip; Tymms, Chase; Bakshy, Eytan; Shvartsman, Michael


• Debiasing Samples from Online Learning Using Bootstrap
  Chen, Ningyuan; GAO, Xuefeng; Xiong, Yi


• Convergence of online k-means
  So, Geelon; Mahajan, Gaurav; Dasgupta, Sanjoy


• Reconstructing Test Labels from Noisy Loss Functions
  Aggarwal, Abhinav; Kasiviswanathan, Shiva; Xu, Zekun; Feyisetan, Oluwaseyi; Teissier, Nathanael


• Contrasting the landscape of contrastive and non-contrastive learning
  Pokle, Ashwini ; Tian, Jinjin; Li, Yuchen; Risteski, Andrej


• A general class of surrogate functions for stable and efficient reinforcement learning
  Vaswani, Sharan; Bachem, Olivier; Totaro, Simone; Müller, Robert ; Garg, Shivam; Geist, Matthieu; C. Machado, Marlos; Castro, Pablo Samuel; Le Roux, Nicolas


• Fundamental limits for rank-one matrix estimation with groupwise heteroskedasticity
  Behne, Joshua K; Reeves, Galen


• Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm
  Bu, Yuheng; Aminian, Gholamali; Toni, Laura; Wornell, Gregory W; Rodrigues, Miguel


• Decoupling Local and Global Representations of Time Series
  Tonekaboni, Sana; Li, Chun-Liang; Arik, Sercan O.; Goldenberg, Anna; Pfister, Tomas


• Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization
  Tran-The, Hung; Gupta, Sunil; Rana, Santu; Venkatesh, Svetha


• Optimal estimation of Gaussian DAG models
  Gao, Ming; Tai, Wai Ming; Aragam, Bryon


• Improved Approximation Algorithms for Individually Fair Clustering
  Vakilian, Ali; Yalciner, Mustafa


• Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning
  Kwon, Yongchan; Zou, James


• Variance Minimization in the Wasserstein Space for Invariant Causal Prediction
  Martinet, Guillaume G; Strzalkowski, Alexander; Engelhardt, Barbara


• Online Continual Adaptation with Active Self-Training
  Zhou, Shiji; Zhao, Han; Zhang, Shanghang; Wang, Lianzhe; Chang, Heng; Wang, Zhi; Zhu, Wenwu


• Structured variational inference in Bayesian state-space models
  Wang, Honggang; Bhattacharya, Anirban ; Pati, Debdeep; Yang, Yun


• Structured Multi-task Learning for Molecular Property Prediction
  Liu, Shengchao; Qu, Meng; Zhang, Zuobai; Cai, Huiyu; Tang, Jian


• Nonparametric Relational Models with Superrectangulation
  Nakano, Masahiro; Nishikimi, Ryo; Fujiwara, Yasuhiro; Kimura, Akisato; Yamada, Takeshi; Ueda, Naonori


• Regret, stability & fairness in matching markets with bandit learners
  Cen, Sarah H; Shah, Devavrat


• Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods
  Agarwal, Chirag; Zitnik, Marinka; Lakkaraju, Himabindu


• Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks
  Li, Yeshu; Shi, Zhan; Zhang, Xinhua; Ziebart, Brian


• ExactBoost: Directly Boosting the Margin in Combinatorial and Non-decomposable Metrics
  Csillag, Daniel; Piazza, Carolina; Ramos, Thiago; Romano, João Vitor; Oliveira, Roberto I; Orenstein, Paulo


• Sharp Bounds for Federated Averaging (Local SGD) and Continuous Perspective
  Glasgow, Margalit R; Yuan, Honglin; Ma, Tengyu


• Near-Optimal Task Selection for Meta-Learning with Mutual Information and Online Variational Bayesian Unlearning
  Chen, Yizhou; Zhang, Shizhuo; Low, Bryan Kian Hsiang


• Best Arm Identification with Safety Constraints
  Wang, Zhenlin; Wagenmaker, Andrew J; Jamieson, Kevin


• On the complexity of the optimal transport problem with graph-structured cost
  Fan, Jiaojiao; Haasler, Isabel; Karlsson, Johan; Chen, Yongxin


• Second-Order Sensitivity Analysis for Bilevel Optimization
  Dyro, Robert; Schmerling, Edward; Arechiga, Nikos; Pavone, Marco


• On Learning Mixture Models with Sparse Parameters
  Pal, Soumyabrata; Mazumdar, Arya


• Sketch-and-lift: scalable subsampled semidefinite program for K-means clustering
  Zhuang, Yubo; Chen, Xiaohui; Yang, Yun


• Asynchronous Distributed Optimization with Stochastic Delays
  Glasgow, Margalit R; Wootters, Mary


• Calibration Error for Heterogeneous Treatment Effects
  Xu, Yizhe; Yadlowsky, Steve


• Fast Sparse Classification for Generalized Linear and Additive Models
  Liu, Jiachang; Zhong, Chudi; Seltzer, Margo; Rudin, Cynthia


• A Unified View of SDP-based Neural Network Verification through Completely Positive Programming
  Brown, Robin A; Schmerling, Edward; Azizan, Navid; Pavone, Marco


• Recoverability Landscape of Tree Structured Markov Random Fields under Symmetric Noise
  Katiyar, Ashish ; Basu, Soumya; Shah, Vatsal; Caramanis, Constantine


• Learning Sparse Fixed-Structure Gaussian Bayesian Networks
  Bhattacharyya, Arnab; Choo, Davin; Gajjala, Rishikesh; Gayen, Sutanu; WANG, Yuhao


• Learning and Generalization in Overparameterized Normalizing Flows
  Shah, Kulin; Deshpande, Amit; Goyal, Navin


• Expressivity of Neural Networks via Chaotic Itineraries beyond Sharkovsky's Theorem
  Sanford, Clayton H; Chatziafratis, Vaggos


• Learning Interpretable, Tree-Based Projection Mappings for Nonlinear Embeddings
  Zharmagambetov, Arman S; Carreira-Perpinan, Miguel A


• Disentangling Whether from When in a Neural Mixture Cure Model for Failure Time Data
  Engelhard, Matthew; Henao, Ricardo


• Sample Complexity of Robust Reinforcement Learning with a Generative Model
  Panaganti, Kishan; Kalathil, Dileep


• On Coresets for Fair Regression and Individually Fair Clustering
  Chhaya, Rachit; Dasgupta, Anirban; Choudhari, Jayesh; Shit, Supratim


• LocoProp: Enhancing BackProp via Local Loss Optimization
  Amid, Ehsan; Anil, Rohan; Warmuth, Manfred


• Towards Agnostic Feature-based Dynamic Pricing: Linear Policies vs Linear Valuation with Unknown Noise
  Xu, Jianyu; Wang, Yu-Xiang


• A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds
  Tan, Yan Shuo; Agarwal, Abhineet; Yu, Bin


• Exact Community Recovery over Signed Graphs
  Wang, Xiaolu; Wang, Peng; So, Anthony Man-Cho


• Laplacian Constrained Precision Matrix Estimation: Existence and High Dimensional Consistency
  Pavez, Eduardo


• Primal-Dual Stochastic Mirror Descent for MDPs
  Tiapkin, Daniil; Gasnikov, Alexander


• Convex Analysis of the Mean Field Langevin Dynamics
  Nitanda, Atsushi; Wu, Denny; Suzuki, Taiji


• Information-Theoretic Analysis of Epistemic Uncertainty in Bayesian Meta-learning
  Jose, Sharu Theresa; Park, Sangwoo; Simeone, Osvaldo


• Marginalising over Stationary Kernels with Bayesian Quadrature
  Hamid, Saad; Schulze, Sebastian; Osborne, Michael A. ; Roberts, Stephen


• On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging
  Li, Chris Junchi; Yu, Yaodong; Loizou, Nicolas; Gidel, Gauthier; Ma, Yi; Le Roux, Nicolas; Jordan, Michael


• An Unsupervised Hunt for Gravitational Lenses
  Sheng, Stephen; G C , Keerthi Vasan; Choi, Chi Po P; Sharpnack, James; Jones, Tucker


• Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics
  Le, Tam; Nguyen, Truyen; Phung, Dinh; Nguyen, Viet Anh


• Mean Nyström Embeddings for Adaptive Compressive Learning
  Chatalic, Antoine; Carratino, Luigi; De Vito, Ernesto; Rosasco, Lorenzo


• GraphAdaMix: Enhancing Node Representations with Graph Adaptive Mixtures
  Tam, Da Sun Handason; Xie, Siyue; Lau, Wing Cheong


• Provable Adversarial Robustness for Fractional Lp Threat Models
  Levine, Alexander J; Feizi, Soheil


• On Some Fast And Robust Classifiers For High Dimension, Low Sample Size Data
  Roy, Sarbojit; Ray Choudhury, Jyotishka; Dutta, Subhajit


• Learning Pareto-Efficient Decisions with Confidence
  Ek, Sofia; Zachariah, Dave; Stoica, Peter


• Efficient and passive learning of networked dynamical systems driven by non-white exogenous inputs
  Doddi, Harish; Deka, Deepjyoti; Talukdar, Saurav; Salapaka, Murti


• Compressed Rule Ensemble Learning
  Nalenz, Malte; Augustin, Thomas


• Pick-and-Mix Information Operators for Probabilistic ODE Solvers
  Bosch, Nathanael; Tronarp, Filip; Hennig, Philipp


• Finite Sample Analysis of Mean-Volatility Actor-Critic for Risk-Averse Reinforcement Learning
  Eldowa, Khaled; Bisi, Lorenzo; Restelli, Marcello


• The Importance of Future Information in Credit Card Fraud Detection
  Nguyen, Van Bach; Ghosh Dastidar, Kanishka; Granitzer, Michael; Siblini, Wissam


• A Non-asymptotic Approach to Best-Arm Identification for Gaussian Bandits
  Barrier, Antoine; Garivier, Aurélien; Kocák, Tomáš


• Differentially Private Federated Learning on Heterogeneous Data
  Noble, Maxence; Bellet, Aurélien; Dieuleveut, Aymeric


• Efficient computation of the the volume of a polytope in high-dimensions using Piecewise Deterministic Markov Processes
  Chevallier, Augustin; Cazals, Frédéric; Fearnhead, Paul


• Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates
  Irons, Nicholas J; Scetbon, Meyer; Pal, Soumik ; Harchaoui, Zaid


• Solving Marginal MAP Exactly by Probabilistic Circuit Transformations
  Choi, YooJung; Friedman, Tal; Van den Broeck, Guy


• REPID: Regional Effect Plots with implicit Interaction Detection
  Herbinger, Julia; Bischl, Bernd; Casalicchio, Giuseppe


• Minimal Expected Regret in Linear Quadratic Control
  Jedra, Yassir; Proutiere, Alexandre


• Data-splitting improves statistical performance in overparameterized regimes
  Muecke, Nicole; Reiss, Enrico; Rungenhagen, Jonas; Klein, Markus


• Towards Understanding Biased Client Selection in Federated Learning
  Cho, Yae Jee; Wang, Jianyu; Joshi, Gauri


• Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications
  Goibert, Morgane; Clemencon, Stephan; Irurozki, Ekhine; Mozharovskyi, Pavlo


• Effective Nonlinear Feature Selection Method based on HSIC Lasso and with Variational Inference
  Koyama, Kazuki; Kiritoshi, Keisuke; Okawachi, Tomomi; Izumitani, Tomonori


• Sobolev Norm Learning Rates for Conditional Mean Embeddings
  Talwai, Prem; Shameli, Ali; Simchi-Levi, David


• Provable Continual Learning via Sketched Jacobian Approximations
  Heckel, Reinhard


• Neural Enhanced Dynamic Message Passing
  Gao, Fei; Zhang, Jiang; zhang, yan


• Duel-based Deep Learning system for solving IQ tests
  Tomaszewska, Paulina; Żychowski, Adam; Mańdziuk, Jacek


• On a Connection Between Fast and Sparse Oblivious Subspace Embeddings
  Wang, Rui; Xu, Wangli


• Modeling Conditional Dependencies in Multiagent Trajectories
  Rudolph, Yannick; Brefeld, Ulf


• Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies
  Minorics, Lenon; Turkmen, Caner; Kernert, David; Bloebaum, Patrick; Callot, Laurent; Janzing, Dominik


• Increasing the accuracy and resolution of precipitation forecasts using deep generative models
  Price, Ilan; Rasp, Stephan


• Tight bounds for minimum $\ell_1$-norm interpolation of noisy data
  Wang, Guillaume; Donhauser, Konstantin; Yang, Fanny


• Multivariate Quantile Function Forecaster
  Kan, Kelvin; Aubet, François-Xavier; Januschowski, Tim ; Park, Youngsuk; Benidis, Konstantinos; Ruthotto, Lars; Gasthaus, Jan


• Coresets for Data Discretization and Sine Wave Fitting
  Maalouf, Alaa; Tukan, Murad; Price, Eric; Kane, Daniel M; Feldman, Dan


• Non-separable Spatio-temporal Graph Kernels via SPDEs
  Nikitin, Alexander V; John, ST; Solin, Arno; Kaski, Samuel


• Towards an Understanding of Default Policies in Multitask Policy Optimization
  Moskovitz, Ted; Arbel, Michael; Parker-Holder, Jack; Pacchiano, Aldo


• Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations
  Kviman, Oskar; Melin, Harald; Koptagel, Hazal; Elvira, Victor; Lagergren, Jens


• Can Functional Transfer Methods Capture Simple Inductive Biases?
  Nix, Arne; Shrinivasan, Suhas; Walker, Edgar Y; Sinz, Fabian


• On the Oracle Complexity of Higher-Order Smooth Non-Convex Finite-Sum Optimization
  Emmenegger, Nicolas; Kyng, Rasmus; N. Zehmakan, Ahad


• Model-agnostic out-of-distribution detection using combined statistical tests
  Bergamin, Federico; Mattei, Pierre-Alexandre; Havtorn, Jakob Drachmann; Sénétaire, Hugo; Schmutz, Hugo; Maaløe, Lars; Hauberg, Soren; Frellsen, Jes


• Generalized Group Testing
  Cheng, Xiwei; Jaggi, Sidharth; Zhou, Qiaoqiao


• Adaptive A/B Test on Networks with Cluster Structures
  Liu, Yang; Zhou, Yifan; Li, Ping; Hu, Feifang


• Spectral Robustness for Correlation Clustering Reconstruction in Semi-Adversarial Models
  Chierichetti, Flavio; Panconesi, Alessandro; Re, Giuseppe; Trevisan, Luca


• Beyond Data Samples: Aligning Differential Networks Estimation with Scientific Knowledge
  Sekhon, Arshdeep; Wang, Zhe; Qi, Yanjun


• Two-way Sparse Network Inference for Count Data
  Li, Sijia; López-García, Martín; Lawrence, Neil D; Cutillo, Luisa


• Rapid Convergence of Informed Importance Tempering
  Zhou, Quan; Smith, Aaron


• On the Implicit Bias of Gradient Descent for Temporal Extrapolation
  Cohen-Karlik, Edo; Ben David, Avichai; Cohen, Nadav; Globerson, Amir


• Differentiable Bayesian inference of SDE parameters using a pathwise series expansion of Brownian motion
  Ghosh, Sanmitra; Birrell, Paul J. ; De Angelis, Daniela


• Quadric Hypersurface Intersection for Manifold Learning in Feature Space
  Pavutnitskiy, Fedor; Ivanov, Sergei O.; Abramov, Evgeniy; Borovitskiy, Viacheslav; Klochkov, Artem; Vyalov, Viktor; Zaikovskii, Anatolii; Petiushko, Aleksandr


• Adaptive Sampling for Heterogeneous Rank Aggregation from Noisy Pairwise Comparisons
  Wu, Yue; Jin, Tao; Lou, Hao; Xu, Pan; Farnoud, Farzad; Gu, Quanquan


• Outcome Assumptions and Duality Theory for Balancing Weights
  Bruns-Smith, David A; Feller, Avi


• Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach
  Ariafar, Setareh; Gilmer, Justin; Nado, Zachary; Snoek, Jasper; Jenatton, Rodolphe; Dahl, George


• Learning from Multiple Noisy Partial Labelers
  Yu, Peilin; Ding, Tiffany; Bach, Stephen H


• Forward Looking Best-Response Multiplicative Weights Update Methods for Bilinear Zero-sum Games
  Fasoulakis, Michail; Markakis, Evangelos; Pantazis, Yannis; Varsos, Constantinos


• Hypergraph Simultaneous Generators
  Pedrood, Bahman; Domeniconi, Carlotta; Laskey, Kathryn


• Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation
  Dyer, Joel; Cannon, Patrick W; Schmon, Sebastian M


• Robust Training in High Dimensions via Block Coordinate Geometric Median Descent
  Acharya, Anish; Hashemi, AbolfazL; Jain, Prateek; Sanghavi, Sujay; Dhillon, Inderjit S.; Topcu, Ufuk


• Stateful Offline Contextual Policy Evaluation and Learning
  Kallus, Nathan; Zhou, Angela


• Sample Complexity of Policy-Based Methods under Off-Policy Sampling and Linear Function Approximation
  Chen, Zaiwei; Maguluri, Siva Theja


• Solving Multi-Arm Bandit Using a Few Bits of Communication
  Hanna, Osama A; Yang, Lin; Fragouli, Christina


• Causal Effect Identification with Context-specific Independence Relations of Control Variables
  Mokhtarian, Ehsan; Jamshidi, Fateme; Etesami, Jalal; Kiyavash, Negar


• Entropy Regularized Optimal Transport Independence Criterion
  Liu, Lang; Pal, Soumik; Harchaoui, Zaid


• Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value Functions
  DENG, ZIHAO; Devic, Siddartha; Juba, Brendan


• PAC Learning of Quantum Measurement Classes : Sample Complexity Bounds and Universal Consistency
  Padakandla, Arun; Magner, Abram


• Can we Generalize and Distribute Private Representation Learning?
  Azam, Sheikh Shams; Kim, Taejin; Hosseinalipour, Seyyedali; Joe-Wong, Carlee; Bagchi, Saurabh; Brinton, Christopher


• Feature Collapsing for Gaussian Process Variable Ranking
  Sebenius, Isaac; Paananen, Topi; Vehtari, Aki


• Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size
  Zhang, Wanrong; Mei, Yajun; Cummings, Rachel


• FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning
  Gasanov, Elnur; Khaled, Ahmed; Horváth, Samuel; Richtarik, Peter


• Data Appraisal Without Data Sharing
  XU, Xinlei; Hannun, Awni; van der Maaten, Laurens


• On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds
  Le, Trung; Bui, Anh Tuan; Minh Tri Tue, LE ; Zhao, He; Montague, Paul; Tran, Quan; Phung, Dinh


• Transductive Robust Learning Guarantees
  Montasser, Omar; Hanneke, Steve; Srebro, Nathan


• Online Competitive Influence Maximization
  Zuo, Jinhang; Liu, Xutong; Joe-Wong, Carlee; Lui, John C. S.; Chen, Wei


• Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff
  Korba, Anna; Portier, François


• The role of optimization geometry in single neuron learning
  Boffi, Nicholas; Tu, Stephen; Slotine, Jean-Jacques


• Learning Tensor Representations for Meta-Learning
  Deng, Samuel; Guo, Yilin; Hsu, Daniel; Mandal, Debmalya


• Differentially Private Densest Subgraph
  Farhadi, Alireza; Hajiaghai, MohammadTaghi; Shi, Elaine


• A Manifold View of Adversarial Risk
  Zhang, Wenjia; Zhang, Yikai; Hu, Xiaoling; Goswami, Mayank; Chen, Chao; Metaxas, Dimitris N.


• Statistical and computational thresholds for the planted k-densest sub-hypergraph problem
  Corinzia, Luca; Penna, Paolo; Szpankowski, Wojciech; Buhmann, Joachim


• Controlling Epidemic Spread using Probabilistic Diffusion Models on Networks
  Babay, Amy E; Dinitz, Michael; Srinivasan, Aravind; Tsepenekas, Leonidas; Vullikanti, Anil


• Equivariant Deep Dynamical Model for Motion Prediction
  Azari, Bahar; Erdogmus, Deniz


• The Fast Kernel Transform
  Ryan, John P; Ament, Sebastian E; Gomes, Carla P; Damle, Anil


• Outlier-Robust Optimal Transport: Duality, Structure, and Statistical Analysis
  Nietert, Sloan; Goldfeld, Ziv; Cummings, Rachel


• Diversity and Generalization in Neural Network Ensembles
  Ortega Andrés, Luis Antonio; Cabañas, Rafael; Masegosa, Andres