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AI & Statistics 2014
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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 Corander

10:00-11:15 Paper Session1 - 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 Girolami

10:00-11:15 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 Kaski

10:00-11:15 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.

12:45 Bus leaves Reykjavik University (front entrance) for Golden Circle tour

13:00 Pickup at Grand Hotel for Golden Circle tour

19:30 Return to Reykjavik

Note: Golden Circle tour includes lunch.