Overview of the ICML, UAI, COLT and MLG 2008 Programme

ICML 2008 UAI 2008 COLT 2008 MLG 2008

Fri 4 July MLG Technical sessions
17:00-19:00 MLG Poster session
20:00-23:00 MLG Banquet

Sat 5 July 9:00-18:30 ICML Tutorials MLG Technical sessions

Sun 6 July 8:30-17:45 ICML Technical sessions
18:00-20:30 ICML Poster session I

Mon 7 July 8:30-17:00 ICML Technical sessions
18:30-22:30 ICML Banquet

Tue 8 July 8:30-17:30 ICML Technical sessions
18:00-20:30 ICML Poster session II

Wed July 9:00-18:00 ICML/UAI/COLT joint workshop day
18:00-20:00 ICML/UAI/COLT joint reception in the Main Building

Thu 10 July 9:00-16:50 UAI Technical sessions 8:30-18:30 COLT Technical sessions
17:15-18:15 UAI Poster Spotlights 18:30-19:00 COLT Open Problem session
18:15-21:00 UAI Poster session 20:00-21:30 COLT Business meeting

Fri 11 July 9:00-18:30 UAI Technical sessions 8:30-19:00 COLT Technical sessions
18:30-20:00 UAI Business meeting 19:00-20:00 COLT Rump session
20:00-23:00 Joint UAI/COLT Banquet

Sat 12 July 9:00-15:30 UAI Technical sessions 8:30-18:00 COLT Technical sessions

UAI 2008 Schedule

All pleanary sessions will take place in lecture room PI of the Porthania building at Yliopistonkatu 3. The program leaflet contains more information about the venue and practical details.

The plenary talks are 20 minutes long each. After each talk there is a 5 minute break for questions and for changing the speaker. (N.B. The session titles are only indicative and do not necessarily reflect accurately the topic of all the papers in the session.)

Thursday, July 10

8:45-9:00 Opening Remarks

9:00-10:15 Topic Models and Clustering (Chair: Mark Johnson)
- David Mimno, Andrew McCallum: Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression
- Amit Gruber, Michal Rosen Zvi, Yair Weiss: Latent Topic Models for Hypertext
- Daniel Tarlow, Richard Zemel, Brendan Frey: Flexible Priors for Exemplar-based Clustering

10:15-10:40 Coffee Break

10:40-11:40 Invited Talk
- Peter Grünwald: The Catch-Up Phenomenon in Bayesian Inference

11:45-13:00 Inference I (Chair: Ben Taskar)
- Tamir Hazan, Amnon Shashua: Convergent Message-Passing Algorithms for Inference over General Graphs with Convex Free Energies (Best student paper runner up)
- David Sontag, Talya Meltzer, Amir Globerson, Tommi Jaakkola, Yair Weiss: Tightening LP Relaxations for MAP using Message Passing (Best paper award)
- Justin Domke: Learning Convex Inference of Marginals

13:00-14:30 Lunch Break (AUAI chairs meeting)

14:30-15:30 Invited Talk
- Robin Hanson: Combinatorial Prediction Markets

15:35-16:50 Games and Decisions (Chair: Stuart Russell)
- Sevan Ficici, David Parkes, Avi Pfeffer: Learning and Solving Many-Player Games through a Cluster-Based Representation
- Enrique Munoz de Cote, Michael Littman: A Polynomial-time Nash Equilibrium Algorithm for Repeated Stochastic Games (Best student paper award)
- Cassio de Campos, Qiang Ji: Strategy Selection in Influence Diagrams using Imprecise Probabilities

16:50-17:15 Coffee Break

17:15-18:15 Poster spotlights - 40 spotlight presentations, 1.5 minutes each, one slide/spotlight

18:15-21:00 Poster session

Friday, July 11

9:00-10:15 Multi-View and Transfer Learning (Chair: Zoubin Ghahramani)
- Kuzman Ganchev, Joao Graca, John Blitzer, Ben Taskar: Multi-View Learning over Structured and Non-Identical Outputs
- C. Mario Christoudias, Raquel Urtasun, Trevor Darrell: Multi-View Learning in the Presence of View Disagreement
- Gal Elidan, Benjamin Packer, Geremy Heitz, Daphne Koller: Convex Point Estimation using Undirected Bayesian Transfer Hierarchies

10:15-10:40 Coffee Break

10:40-11:40 Invited Talk
- Gabor Lugosi: Concentration inequalities

11:45-13:00 Reinforcement learning (Chair: Rich Sutton)
- Emma Brunskill, Bethany Leffler, Lihong Li, Michael Littman, Nicholas Roy: CORL: A Continuous-state Offset-dynamics Reinforcement Learner
- Branislav Kveton, Milos Hauskrecht: Partitioned Linear Programming Approximations for MDPs
- Marc Toussaint, Laurent Charlin, Pascal Poupart: Hierarchical POMDP Controller Optimization by Likelihood Maximization (Best paper runner up)

13:00-14:30 Lunch Break

14:30-15:30 Invited Talk
- Dan Klein: Unsupervised Learning for Natural Language Processing

15:35-16:50 Causality (Chair: Andrew Ng)
- Ulf Nielsen, Jean-Philippe Pellet, André Elisseeff: Explanation Trees for Causal Bayesian Networks
- A. Philip Dawid, Vanessa Didelez: Identifying Optimal Sequential Decisions
- Jin Tian: Identifying Dynamic Sequential Plans

16:50-17:15 Coffee Break

17:15-18:30 Network learning (Chair: Pascal Poupart)
- Harald Steck: Learning the Bayesian Network Structure: Dirichlet Prior vs. Data
- Gustavo Lacerda, Peter Spirtes, Joseph Ramsey, Patrik Hoyer: Discovering Cyclic Causal Models by Independent Components Analysis
- Varun Ganapathi, David Vickrey, John Duchi, Daphne Koller: Constrained Approximate Maximum Entropy Learning of Markov Random Fields

18:30-19:55 UAI Business Meeting

20:00-23:00 UAI/COLT Joint Banquet

Saturday, July 12

9:00-10:15 Modeling and Regression (Chair: Amir Globerson)
- Keith Noto, Mark Craven: Learning Hidden Markov Models for Regression using Path Aggregation
- Seyoung Kim, Eric Xing: Feature Selection via Block-Regularized Regression
- David Barber: Clique Matrices for Statistical Graph Decomposition and Parameterising Restricted Positive Definite Matrices

10:15-10:40 Coffee Break

10:40-12:20 Inference II (Chair: Tommi Jaakkola)
- Arthur Choi, Adnan Darwiche: Approximating the Partition Function by Deleting and then Correcting for Model Edges
- Venkat Chandrasekaran, Nathan Srebro, Prahladh Harsha: Complexity of Inference in Graphical Models
- Peter Thwaites, Jim Smith, Robert Cowell: Propagation using Chain Event Graphs
- Tal El-Hay, Nir Friedman, Raz Kupferman: Gibbs Sampling in Factorized Continuous-Time Markov Processes (Best student paper runner up)

12:20-13:50 Lunch Break

13:50-15:30 Modeling (Chair: Hal Daume)
- Noah Goodman, Vikash Mansinghka, Daniel Roy, Keith Bonawitz, Joshua Tenenbaum: Church: a language for generative models
- Mathias Niepert, Dirk Van Gucht, Marc Gyssens: On the Conditional Independence Implication Problem: A Lattice-Theoretic Approach (Best student paper runner up)
- Hannaneh Hajishirzi, Eyal Amir: Sampling First Order Logical Particles
- Jim Huang, Brendan Frey: Cumulative distribution networks and the derivative-sum-product algorithm (Best student paper runner up)

15:30 End of the conference

Accepted UAI posters

The poster session takes place on Thursday, July 10, at 5:15pm-9pm (starting with a one hour poster spotlight session).

01 Umut A. Acar, Alexander Ihler, Ramgopal R. Mettu, Özgür Sumer Adaptive inference on general graphical models
02 Dimitrios Antos, Avi Pfeffer Identifying reasoning patterns in games
03 Vincent Auvray, Louis Wehenkel Learning Inclusion-Optimal Chordal Graphs
04 Debarun Bhattacharjya, Ross Shachter Sensitivity analysis in decision circuits
05 Liefeng Bo, Cristian Sminchisescu Greedy Block Coordinate Descent for Large Scale Gaussian Process Regression
06 Zhihong Cai, Manabu Kuroki On Identifying Total Effects in the Presence of Latent Variables and Selection bias
07 Botond Cseke, Tom Heskes Bounds on the Bethe Free Energy for Gaussian Networks
08 James Cussens Bayesian network learning by compiling to weighted MAX-SAT
09 Gert De Cooman, Filip Hermans, Erik Quaeghebeur Sensitivity analysis for finite Markov chains in discrete time
10 John Duchi, Stephen Gould, Daphne Koller Projected Subgradient Methods for Learning Sparse Gaussians
11 Quang Duong, Michael Wellman, Satinder Singh Knowledge Combination in Graphical Multiagent Models
12 Frederick Eberhardt Almost Optimal Intervention Sets for Causal Discovery
13 Vibhav Gogate, Rina Dechter AND/OR Importance Sampling
14 Peter Grunwald, Joe Halpern A Game-Theoretic Analysis of Updating Sets of Probabilities
15 Eric Hansen Sparse Stochastic Finite-State Controllers for POMDPs
16 Greg Hines, Kate Larson Learning When to Take Advice: A Statistical Test for Achieving A Correlated Equilibrium
17 Patrik Hoyer, Aapo Hyvarinen, Richard Scheines, Peter Spirtes, Joseph Ramsey, Gustavo Lacerda, Shohei Shimizu Causal discovery of linear acyclic models with arbitrary distributions
18 Bowen Hui, Craig Boutilier Toward Experiential Utility Elicitation for Interface Customization
19 Alejandro Isaza, Csaba Szepesvari, Vadim Bulitko, Russell Greiner Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstraction
20 Tony Jebara Bayesian Out-Trees
21 Manabu Kuroki, Zhihong Cai The Evaluation of Causal Effects in Studies with an Unobserved Exposure/Outcome Variable: Bounds and Identification
22 Johan Kwisthout, Linda van der Gaag The Computational Complexity of Sensitivity Analysis and Parameter Tuning
23 Eric Laber, Susan Murphy Small Sample Inference for Generalization Error in Classification Using the CUD Bound
24 Gregory Lawrence, Stuart Russell Improving Gradient Estimation by Incorporating Sensor Data
25 Daniel Lowd, Pedro Domingos Learning Arithmetic Circuits
26 Marina Meila, Le Bao Estimation and clustering with infinite rankings
27 Kurt Miller, Thomas Griffiths, Michael I. Jordan The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Features
28 Lars Otten, Rina Dechter Bounding Search Space Size via (Hyper)tree Decompositions
29 Yan Radovilsky, Eyal Shimony Observation Subset Selection as Local Compilation of Performance Profiles
30 Sebastian Riedel Improving the Accuracy and Efficiency of MAP Inference for Markov Logic
31 Stephane Ross, Joelle Pineau Model-Based Bayesian Reinforcement Learning in Large Structured Domains
32 Aleksandr Simma, Moises Goldszmidt, John MacCormick, Paul Barham, Richard Black, Rebecca Isaacs, Richard Mortier CT-NOR: Representing and Reasoning About Events in Continuous Time
33 Tomas Singliar, Denver Dash Efficient Inference in Persistent Dynamic Bayesian Networks
34 Matthew Streeter, Stephen Smith New Techniques for Algorithm Portfolio Design
35 Richard Sutton, Csaba Szepesvari, Alborz Geramifard, Michael Bowling Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
36 Jarno Vanhatalo, Aki Vehtari Modelling local and global phenomena with sparse Gaussian processes
37 Chong Wang, David Blei, David Heckerman Continuous Time Dynamic Topic Models
38 Max Welling, Yee Whye Teh, Bert Kappen Hybrid Variational/Gibbs Collapsed Inference in Topic Models
39 Ydo Wexler, Christopher Meek Inference for Multiplicative Models
40 Haohai Yu, Robert van Engelen Refractor Importance Sampling