UAI Main Conference Program

July 12th-14th

All talks and banquet will be held in Grand Ballroom B and C on the Third Level of the Westin Hotel. Poster sessions will be held in the foyer area outside the Grand Ballroom.

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Schedule

Day 1 - Friday July 12th

Day 2 - Saturday July 13th

Day 3 - Sunday July 14th

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Friday July 12th

7:30am - 8:30am: Breakfast

8:30am – Welcome and Opening Remarks

Keynote Talk

8:40am – Never Ending Learning
Tom Mitchell, CMU

Session 1: Classification (Chair: Amir Globerson)

Session chair: Amir Globerson
9:40am – Modeling Documents with Deep Boltzmann Machines
Nitish Srivastava, Ruslan Salakhutdinov, Geoffrey Hinton
10:05am – Generative Multiple-Instance Learning Models For Quantitative Electromyography
Tameem Adel, Ruth Urner, Benn Smith, Daniel Stashuk, Dan Lizotte

10:30 – Coffee Break

Session 2: Structure Learning (Chair: Petri Myllamaki)

11:00am – Advances in Bayesian Network Learning using Integer Programming
James Cussens, Mark Bartlett
11:25am – Treedy: A Heuristic for Counting and Sampling Subsets
Teppo Niinimäki, Mikko Koivisto
11:50am – Evaluating Anytime Algorithms for Learning Optimal Bayesian Networks
Brandon Malone, Changhe Yuan

12:15 – Lunch (on your own)

Session 3a: Stochastic Processes (Chair: Scott Sanner)

2:00pm – Learning Periodic Human Behaviour Models from Sparse Data for Crowdsourcing Aid Delivery in Developing Countries
James McInerney, Alex Rogers, Nicholas Jennings
2:25pm – Hilbert Space Embeddings of Predictive State Representations
Byron Boots, Geoffrey Gordon, Arthur Gretton

Session 3b: Novel Modeling Approaches (Chair: Scott Sanner)

2:50pm – On the Complexity of Strong and Epistemic Credal Networks
Denis Maua, Cassio de Campos, Alessio Benavoli, Alessandro Antonucci
3:15pm – Sparse Nested Markov models with Log-linear Parameters
Ilya Shpitser, Robin Evans, Thomas Richardson, James Robins

Poster Spotlights 1 (Chair: Vibhav Gogate)

3:40pm – 1 minute poster spotlight presentations from papers 248, 61, 80, 146, 176, 30, 47, 63, 66, 76, 88, 225, 37, 151, 161, 54.

4pm to 6pm – Poster Session 1 and Coffee Break

All oral presentations from Friday and all poster spotlights.

7pm – Conference Banquet

Banquet Talk: Research and Consumer Products - Yoky Matsuoka

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Saturday July 13th

7:30am - 8:30am: Breakfast

Keynote Talk

8:30am – Bayesian Learning in Online Service: Statistics Meets Systems
Ralf Herbrich, Amazon

Session 4: Ranking and Semi-Supervised Learning (Chair: Tony Jebara)

9:40am – The Lovasz Bregman Divergences and connections to rank aggregation, clustering and web ranking
Rishabh Iyer, Jeff Bilmes
10:05am – Active Learning with Expert Advice
Peilin Zhao, Steven Hoi, Jinfeng Zhuang

10:30 – Coffee Break

Session 5: Inference Algorithms (Chair: Daniel Lowd)

11:00am – Optimization With Parity Constraints: From Binary Codes to Discrete Integration
Stefano Ermon, Carla Gomes, Ashish Sabharwal, Bart Selman
11:25am – Structured Message Passing
Vibhav Gogate, Pedro Domingos
11:50am – Lower Bounds for Exact Model Counting and Applications in Probabilistic Databases
Paul Beame, Jerry Li, Sudeepa Roy, Dan Suciu

12:15 – Lunch (on your own)

Session 6a: Causal Models (Chair: Thomas Richardson)

2:00pm – Learning Sparse Causal Models is not NP-hard
Tom Claassen, Joris Mooij, Tom Heskes
2:25pm – Cyclic Causal Discovery from Continuous Equilibrium Data
Joris Mooij, Tom Heskes

Session 6b: Learning (Chair: Thomas Richardson)

2:50pm – Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality
Vikas Sindhwani, Minh Ha Quang, Aurelie Lozano
3:15pm – Constrained Bayesian Inference for Low Rank Multitask Learning
Oluwasanmi Koyejo, Joydeep Ghosh

Poster Spotlights 2 (Chair: Denver Dash)

3:40pm – 1 minute poster spotlight presentations from papers 4, 8, 132, 109, 110, 118, 192, 131, 197, 103, 199, 244, 24, 70, 189.

4pm to 6pm – Poster Session 2 and Coffee Break

All oral presentations from Saturday and all poster spotlights.

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Sunday July 14th

7:30am - 8:30am: Breakfast

Keynote Talk

8:30am – Modeling Common-Sense Scene Understanding with Probabilistic Programs
Josh Tenenbaum, MIT

Session 7: Modeling Human Behavior (Chair: Kathy Laskey)

9:40am – Active Sensing as Bayes-Optimal Sequential Decision Making
Sheeraz Ahmad, Angela Yu
10:05am – Evaluating computational models of explanation using human judgments
Michael Pacer, Joseph Williams, Xi Chen, Tania Lombrozo, Thomas Griffiths

10:30 – Coffee Break

Session 8: Markov Decision Processes (Chair: Ron Parr)

11:00am – Bounded Approximate Symbolic Dynamic Programming for Hybrid MDPs
Luis Gustavo Vianna, Scott Sanner, Leliane de Barros
11:25am – Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes
Judy Goldsmith, Josiah Hanna, Patrice Perny, Paul Weng
11:50am – POMDPs under Probabilistic Semantics
Krishnendu Chatterjee, Martin Chmelík

12:15 – Lunch (on your own)

Session 9: Inference Algorithms (Chair: Tom Claassen)

2:00pm – Bethe-ADMM for Tree Decomposition based Parallel MAP Inference
Qiang Fu, Huahua Wang, Arindam Banerjee
2:25pm – On MAP Inference by MWSS on Perfect Graphs
Adrian Weller, Tony Jebara
2:50pm – Automorphism Groups of Graphical Models and Lifted Variational Inference
Hung Bui, Tuyen Huynh, Sebastian Riedel

3:15pm – Business Meeting

Poster Spotlights 3 (Chair: Nevin Zhang)

3:40pm – 1 minute poster spotlight presentations from papers 135, 143, 134, 200, 144, 167, 14, 106, 139, 188, 21, 221, 240, 93, 35, 148.

4pm to 6pm – Poster Session 3 and Coffee Break

All oral presentations from Sunday and all poster spotlights.