UAI Main Conference Program
July 24th-26th
All the conference talks will be held in the Room 306AB on the third level of the Quebec City Convention Centre. Poster sessions, breakfast and coffee breaks will be located in the Hall 310.
Schedule |
Day 1 - Thursday, July 24th |
Day 2 - Friday, July 25th |
Day 3 - Saturday, July 26th |
Thursday, July 24th
8:30am – WelcomeKeynote Talk
8:40am – Probabilistic Topic Models and User BehaviorDavid M. Blei, Columbia University
Session 1: Topic Models and Nonparametric Bayes (Chair: Jeffrey A. Bilmes)
9:40am – 77: Annealing Paths for the Evaluation of Topic ModelsJames Foulds, Padhraic Smyth
10:05am – 107: Bayesian Optimization with Unknown Constraints
Michael Gelbart, Jasper Snoek, Ryan Adams
Session 2: Bayesian Methods and Regression (Chair: Yuhong Guo)
11:00am – 159: Collaborative Multi-output Gaussian ProcessesTrung Nguyen, Edwin Bonilla
11:25am – 283: k-NN Regression on Functional Data with Incomplete Observations
Sashank J. Reddi
11:50am – 302: Firefly Monte Carlo: Exact MCMC with Subsets of Data (Microsoft Best Paper)
Dougal Maclaurin, Ryan Adams
Keynote Talk
2:00pm – Addressing the Practical Challenges of Group Decision Support in a Data-Rich WorldCraig Boutilier, University of Toronto
Session 3: Decision Theory (Chair: Prakash Shenoy)
3:00pm – 321: Electing the Most Probable Without Eliminating the Irrational: Voting Over Intransitive DomainsEdith Elkind, Nisarg Shah
3:25pm – 273: Market Making with Decreasing Utility for Information
Miroslav Dudik, Rafael Frongillo, Jennifer Wortman Vaughan
3:50pm - Poster Spotlights 1 (Chair: Daniel Lowd)
1 minute poster spotlight presentations from papers 37, 39, 58, 64, 74, 110, 117, 152, 154, 166, 171, 179, 182, 199, 213, 219, 220, 227, 229, 231, 303, 3354:15pm - 6:15pm Poster Session 1
All oral presentations from Thursday and all poster spotlights. (Posters can be put up any time during day and need to be removed after the session.)Friday, July 25th
Keynote Talk
8:30am – Planning In The Context Of Model-based Reinforcement LearningMichael L. Littman, Brown University
Session 4: Markov Decision Processes and Reinforcement Learning (Chair: Pascal Poupart)
9:30am – 324: Off-policy TD($\l$) with a true online equivalenceHado Van Hasselt, Rupam Mahmood, Rich Sutton
9:55am – 207: Optimal Resource Allocation with Semi-Bandit Feedback (Best Paper Runner-Up)
Tor Lattimore, Koby Crammer, Csaba Szepesvari
10:20am – 72: Sequential Bayesian Optimisation for Spatial-Temporal Monitoring
Roman Marchant, Fabio Ramos, Scott Sanner
Session 5: Causal Discovery (Chair: David Poole)
11:15am – 176: Inferring latent structures via information inequalitiesRafael Chaves, Lukas Luft, Thiago Maciel, David Gross, Dominik Janzing, Bernhard Schölkopf
11:40am – 87: Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming
Antti Hyttinen, Frederick Eberhardt, Matti Järvisalo
12:05pm – 209: Constructing Separators and Adjustment Sets in Ancestral Graphs (IBM Best Student Paper)
Benito van der Zander, Maciej Liskiewicz, Johannes Textor
Vibhav Gogate, University of Texas at Dallas
Session 6: Approximate Inference (Chair: Rina Dechter)
3:00pm - 215: Lifted Message Passing as Reparametrization of Graphical ModelsMartin Mladenov, Kristian Kersting, Amir Globerson
3:25pm – 168: Tightness Results for Local Consistency Relaxations in Continuous MRFs
Yoav Wald, Amir Globerson
3:50pm - Poster Spotlights 2 (Chair: Changhe Yuan)
1 minute poster spotlight presentations from papers 19, 36, 59, 80, 91, 101, 115, 125, 129, 132, 135, 164, 205, 206, 222, 232, 251, 258, 260, 286, 290, 316, 317, 3364:15pm - 6:15pm Poster Session 2
All oral presentations from Friday and all poster spotlights. (Posters can be put up any time during day and need to be removed after the session)Banquet Talk: The unreasonable effectiveness of deep learning
Yann LeCun, Facebook AI Research & Center for Data Science, NYUSaturday, July 26th
Keynote Talk
8:30am – The Online Revolution: Education for EveryoneAndrew Ng, Stanford University
Session 7: Supervised, Semi-Supervised and Active Learning (Chair: Dale Schuurmans)
9:30am – 98: Learning from Point Sets with Observational BiasLiang Xiong, Jeff Schneider
9:55am – 313: Estimating Accuracy from Unlabeled Data
Emmanouil Antonios Platanios, Avrim Blum, Tom Mitchell
10:20am – 223: Near-optimal Adaptive Pool-based Active Learning with General Loss (Google Best Student Paper)
Nguyen Viet Cuong, Wee Sun Lee, Nan Ye
Session 8: Structure Learning and Exact Inference (Chair: Petri Myllymaki)
11:15am – 194: A Permutation-Based Kernel Conditional Independence TestGary Doran, Krikamol Muandet, Kun Zhang, Bernhard Schölkopf
11:40am – 292: There IS a Free Lunch: Constraints for Learning Bayesian Networks
Xiannian Fan, Brandon Malone; Changhe Yuan
12:05pm – 183: AND/OR Search for Marginal MAP
Radu Marinescu, Rina Dechter, Alexander Ihler
Session 9: Optimization Algorithms (Chair: Ping Li)
2:15pm - 161: Matroid Bandits: Fast Combinatorial Optimization with LearningBranislav Kveton, Zheng Wen, Azin Ashkan, Hoda Eydgahi, Brian Eriksson
2:40pm - 121: Universal Convexification via Risk-Aversion (Facebook Best Student Paper)
Krishnamurthy Dvijotham, Maryam Fazel, Emanuel Todorov
3:05pm – 312: Fast Newton methods for the group fused lasso
Matt Wytock, J. Zico Kolter, Suvrit Sra