UAI 2009 Accepted papers

Yi Mao, Guy Lebanon. Domain Knowledge Uncertainty and Probabilistic Parameter Constraints

Jacek Kisynski, David Poole. Constraint Processing in Lifted Probabilistic Inference

Daniel Andrade, Bernhard Sick. Lower Bound Bayesian Networks - Efficient Inference of Lower Bounds on Probability Distributions

Blai Bonet. Partially Observable Deterministic Processes

Kenichi Kurihara, Shu Tanaka, Seiji Miyashita. Quantum Annealing for Clustering

Yevgeniy Vorobeychik. Simulation-Based Game Theoretic Analysis of Keyword Auctions with Low-Dimensional Bidding Strategies

The Truyen Tran, Dinh Phung, Svetha Venkatesh. Ordinal Boltzmann Machines for Collaborative Filtering

M. Pawan Kumar, Daphne Koller. MAP Estimation of Semi-Metric MRFs via Hierarchical Graph Cuts

Pekka Parviainen, Mikko Koivisto. Exact Structure Discovery in Bayesian Networks with Less Space

Samantha Kleinberg, Bud Mishra. The Temporal Logic of Causal Structures

Siwei Lyu. Interpretation and Generalization of Score Matching

Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh. Multiple Source Adaptation and the Renyi Divergence

Oleg Kiselyov, Chung-chieh Shan. Monolingual Probabilistic Programming Using Generalized Coroutines

Hal Daume. Bayesian Multitask Learning with Latent Hierarchies

Matthias Thimm. Measuring Inconsistency in Probabilistic Knowledge Bases

Mark Crowley, David Poole. Seeing the Forest Despite the Trees: Large Scale Spatial-Temporal Decision Making

Issei Sato, Kenichi Kurihara, Shu Tanaka, Hiroshi Nakagawa , Seiji Miyashita. Quantum Annealing for Variational Bayes Inference

Kun Zhang, Aapo Hyvarinen. On the Identifiability of the Post-Nonlinear Causal Model

Shohei Shimizu, Aapo Hyvarinen, Yoshinobu Kawahara, Takashi Washio. A direct method for estimating a causal ordering in a linear non-Gaussian acyclic model

Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu. A Bayesian Framework for Community Detection Integrating Content and Link

Ilya Shpitser, Judea Pearl. Effects of Treatment on the Treated: Identification and Generalization

Jonas Peters, Dominik Janzing, Joris Mooij, Bernhard Schoelkopf. Identifying confounders using additive noise models

Patrik Hoyer, Antti Hyttinen. Bayesian Discovery of Linear Acyclic Causal Models

Tony Jebara. MAP Estimation, Message Passing, and Perfect Graphs

Daniil Ryabko. Characterizing predictable classes of processes

Vicenc Gomez, Bert Kappen, Misha Chertkov. Approximate inference on planar graphs using Loop Calculus and Belief Propagation

Prithviraj Sen, Amol Deshpande, Lise Getoor. Bisimulation-based Approximate Lifted Inference

Changhe Yuan, Xiaolu Liu, Tsai-Ching Lu, Heejin Lim. Most Relevant Explanation: Properties, Algorithms, and Evaluations

Peter Bartlett, Ambuj Tewari. REGAL: A Regularization based Algorithm for Reinforcement Learning in Weakly Communicating MDPs

Armen Allahverdyan, Aram Galstyan. On Maximum a Posteriori Estimation of Hidden Markov Processes

Michael Finegold, Mathias Drton. Robust Graphical Modelling with t-Distributions

Finale Doshi-Velez, Zoubin Ghahramani. Correlated Non-Parametric Latent Feature Models

David Wingate, Noah Goodman, Daniel Roy, Josh Tenenbaum. The Infinite Latent Events Model

David Bradley, J. Andrew Bagnell. Convex Coding

Ping Li. Improving Compressed Counting

Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh. L_2 Regularization for Learning Kernels

Ido Cohn, Tal El-hay, Raz Kupferman, Nir Friedman. Mean Field Variational Approximation for Continuous-Time Bayesian Networks

Kevin Regan, Craig Boutilier. Regret-based Reward Elicitation for Markov Decision Processes

Fabio Cozman, Rodrigo Polastro. Complexity Analysis and Variational Inference for Interpretation-based Probabilistic Description Log

Thomas Walsh, Istvan Szita, Carlos Diuk, Michael Littman. Exploring compact reinforcement-learning representations with linear regression

Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme. BPR: Bayesian Personalized Ranking from Implicit Feedback

Kuzman Ganchev, Michael Kearns, Yuriy Nevmyvaka, Jennifer Wortman. Censored Exploration and the Dark Pool Problem

Alexandre Bouchard-Cote, Mike Jordan. Optimization of Structured Mean Field Objectives

Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman. Convexifying the Bethe Free Energy

Christian Fritz, Sheila McIlraith. Generating Optimal Plans in Highly-Dynamic Domains

Jun Liu, Shuiwang Ji, Jieping Ye. Accelerated Multi-task Feature Learning

Peter Hooper, Yasin Abbasi-Yadkori, Bret Hoehn, Russell Greiner. Improved Mean and Variance Approximations for Belief Net Response via Network Doubling

Yu Fan, Christian Shelton. Learning Continuous-Time Social Network Dynamics

Talya Meltzer, Amir Globerson, Yair Weiss. Convergent message passing algorithms - a unifying view

Graham Taylor, Geoffrey Hinton. Products of Hidden Markov Models: It Takes N>1 to Tango

Geoffrey Gordon, Sue Ann Hong, Miroslav Dudik. First-Order Mixed Integer Linear Programming

Kristian Kersting, Babak Ahmadi, Sriraam Natarajan. Counting Belief Propagation

Mathias Niepert. Inference Algorithms and Matrix Representations for Probabilistic Conditional Independence

Albert Xin Jiang, Kevin Leyton-Brown, Avi Pfeffer. Temporal Action-Graph Games: A New Representation for Dynamic Games

Mark Schmidt, Kevin Murphy. Modeling Discrete Interventional Data using Directed Cyclic Graphical Models

Jordan Boyd-Graber, David Blei. Multilingual Topic Models for Unaligned Text

Shankar Vembu, Thomas Gartner, Mario Boley. Probabilistic Structured Predictors

Vincent Conitzer. Prediction Markets, Mechanism Design, and Cooperative Game Theory

Max Welling. Herding Dynamic Weights in Random Field Models

Alina Beygelzimer, John Langford, Yury Lifshits, Gregory Sorkin, Alex Strehl. Conditional Probability Tree Estimation Analysis and Algorithms

Sara Mostafavi, Quaid Morris. Using hierarchical information in predicting gene function

Jin Yu, S V N Vishwanathan, Jian Zhang. The Entire Quantile Path of a Risk-Agnostic SVM Classifier

Kedar Bellare, Gregory Druck, Andrew McCallum. Alternating Projections for Learning with Expectation Constraints

Joseph Gonzalez, Yucheng Low, Carlos Guestrin, David O'Hallaron. Distributed Parallel Inference on Large Factor Graphs

Nakul Verma, Samory Kpotufe, Sanjoy Dasgupta. Which Spatial Partition Trees are Adaptive to Intrinsic Dimension?

Michael Littman, Lihong Li, Ali Nouri, David Wingate, John Asmuth. A Bayesian Sampling Approach to Exploration in Reinforcement Learning

Benjamin Lubin, David Parkes. Quantifying the Strategyproofness of Mechanisms via Metrics on Payment Distributions

Vigorito Christopher. Temporal Difference Networks for Dynamical Systems with Continuous Observations and Actions

Matt Hoffman, Hendrik Kueck, Nando de Freitas, Arnaud Doucet. Solving Markov Decision Processes using reversible jump MCMC with auxiliary noise variables

Thomas Richardson. A factorization criterion for acyclic directed mixed graphs

Benjamin Marlin, Kevin Murphy, Mark Schmidt. Sparse Precision Distributions for Covariance Estimation

Miroslav Dudik, Geoffrey Gordon. A Sampling-Based Approach to Computing Equilibria in Succinct Extensive-Form Games

Jin Tian, Ru He. Computing Posterior Probabilities of Structural Features in Bayesian Networks

Arthur Asuncion, Max Welling, Padhraic Smyth, Yee Whye Teh. On Smoothing and Inference for Topic Models

Reza Bosagh Zadeh, Shai Ben-David. A Uniqueness Theorem for Clustering

Thomas Minka, Rongjing Xiang, Nan Ding, Alan Qi. Virtual Vector Machine for Bayesian Online Classification