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AISTATS*2014 Schedule
Main details:
- Conference starts on Tuesday Apr 22 with registration at 8:00 am.
- Social outing to Blue Lagoon and conference dinner on Wednesday Apr 23 afternoon/evening.
- Conference closes Thursday Apr 24 with a joint AISTATS/MLSS poster session with refreshments.
- AISTATS/MLSS tutorials on Friday Apr 25.
The online proceedings and the abstracts of highlight talks
are available through the Talks and Papers page.
Monday, 21 April
17:00-20:00 Registration
Tuesday, 22 April
8:00-9:00 Registration
9:00-10:00 Keynote: Peter Bühlmann, High-dimensional Causal Inference
Session chair: Jukka Corander10:00-11:15 Paper Session 1 - Gaussian processes
Session chair: Aki Vehtari- T01 Explicit Link Between Periodic Covariance Functions and State Space Models
Arno Solin, Simo Särkkä - T02 A Stepwise uncertainty reduction approach to constrained global optimization
Victor Picheny - Highlight talk: H01 Gaussian Processes for Data-Efficient Learning in Robotics and Control
Marc Deisenroth, Dieter Fox, Carl Rasmussen
11:15-13:25 Poster Session 1
See the list of posters.13:25-15:25 Lunch break
(Poster session may continue into the lunch break if needed)15:25-17:05 Paper Session 2 - Graphical models
Session chair: Helene Massam- T03 An inclusion optimal algorithm for chain graph structure learning
Jose Peña, Dag Sonntag, Jens Nielsen - T04 On the Testability of Models with Missing Data
Karthika Mohan, Judea Pearl - T05 Nonparametric estimation and testing of exchangeable graph models
Justin Yang, Christina Han, Edoardo Airoldi - T06 Learning Optimal Bounded Treewidth Bayesian Networks via Maximum Satisfiability
Jeremias Berg, Matti Järvisalo, Brandon Malone
17:05-17:35 Coffee
17:35-18:50 Paper Session 3 - Inference for data from mixed sources
Session chair: Antti Honkela- T07 Bayesian Nonparametric Poisson Factorization for Recommendation Systems
Prem Gopalan, Francisco J. Ruiz, Rajesh Ranganath, David Blei - T21 LAMORE: A Stable, Scalable Approach to Latent Vector Autoregressive Modeling of Categorical Time Series
Yubin Park, Carlos Carvalho, Joydeep Ghosh - Notable paper: T09 Decontamination of Mutually Contaminated Models
Gilles Blanchard, Clayton Scott
Wednesday, 23 April
8:00-9:00 Registration
9:00-10:00 Keynote: Andrew Gelman, Weakly Informative Priors: When a little information can do a lot of regularizing
Session chair: Mark Girolami10:00-11:15 Paper Session 4 - Scientific data analysis
Session chair: Guido Sanguinetti- T10 Towards building a Crowd-Sourced Sky Map
Dustin Lang, David Hogg, Bernhard Schölkopf - T11 Dynamic Resource Allocation for Optimizing Population Diffusion
Shan Xue, Alan Fern, Daniel Sheldon - Highlight talk: H02 Bayesian Monitoring for the Comprehensive Nuclear-Test-Ban Treaty
Stuart Russell, Erik Sudderth, Nimar Arora
11:15-11:45 Coffee
11:45-13:00 Paper Session 5 - Active and online learning
Session chair: Marc Deisenroth- T12 An Analysis of Active Learning with Uniform Feature Noise
Aaditya Ramdas, Barnabas Poczos, Aarti Singh, Larry Wasserman - T13 On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning
Matthew Hoffman, Bobak Shahriari, Nando de Freitas - T14 Selective Sampling with Drift
Edward Moroshko, Koby Crammer
13:00-16:00 Lunch break
The visit to the Blue Lagoon has two departure times, depending on whether you registered for the conference dinner and bath, or for the conference dinner only.16:30 Bus leaves from Grand Hotel (front entrance) for Blue Lagoon, including bath
18:15 Bus leaves from Grand Hotel (front entrance) for Blue Lagoon, for dinner only
19:00-22:00 Dinner at Blue Lagoon
Thursday, 24 April
8:00-9:00 Registration
9:00-10:00 Keynote: Michael I. Jordan, On the Computational and Statistical Interface and "Big Data"
Session chair: Samuel Kaski10:00-11:15 Paper Session 6 - Deep and large-scale learning
Session chair: Nir Ailon- T15 Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data
Abhimanu Kumar, Alex Beutel, Qirong Ho, Eric Xing - Notable paper: T16 Distributed optimization of deeply nested systems
Miguel Carreira-Perpinan, Weiran Wang - Highlight talk: H03 Representation Learning: A Review and New Perspectives
Yoshua Bengio
11:15-11:45 Coffee
11:45-13:00 Paper Session 7 - Kernel methods and matrix factorization
Session chair: Matthew Blaschko- T17 Efficient Algorithms and Error Analysis for the Modified Nystrom Method
Shusen Wang, Zhihua Zhang - T18 Efficiently Enforcing Diversity in Multi-Output Structured Prediction
Abner Guzman-Rivera, Pushmeet Kohli, Dhruv Batra, Rob Rutenbar - T19 Scalable Collaborative Bayesian Preference Learning
Mohammad Emtiyaz Khan, Young Jun Ko, Matthias Seeger
13:00-15:00 Lunch break
15:00-16:40 Paper Session 8 - Approximative inference and Monte Carlo methods
Session chair: Christian Robert- Highlight talk: H04 Spatiotemporal point process models of conflicts
Andrew Zammit-Mangion, Michael Dewar, Visakan Kadirkamanathan, Guido Sanguinetti - T20 Black Box Variational Inference
Rajesh Ranganath, Sean Gerrish, David Blei - T08 Mixed Graphical Models via Exponential Families
Eunho Yang, Yulia Baker, Pradeep Ravikumar, Genevera Allen, Zhandong Liu - T22 A New Approach to Probabilistic Programming Inference
Frank Wood, Jan Willem van de Meent, Vikash Mansinghka
16:40-17:10 Coffee
17:10-20:00 Joint MLSS/AISTATS Poster Session (with some food)
See the list of AISTATS posters.Friday, 25 April
8:00-9:00 Registration
9:00-11:00 Tutorial 1: Roderick Murray-Smith, Machine Learning and Human Computer Interaction
11:00-11:30 Coffee
11:30-13:30 Tutorial 2: Christian P. Robert, Approximate Bayesian computation (ABC), methodology and applications
13:30-15:00 Lunch break
15:00-17:00 Tutorial 3: Håvard Rue, Bayesian computing with INLA
17:30-20:00 MLSS Poster session
Sunday, 27 April
The following schedule items apply to people who registered for the optional AISTATS/MLSS Conference tour to the Golden Circle.