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UAI 2009 Proceedings

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

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

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

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

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

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

Deterministic POMDPs Revisited
Blai Bonet

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

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

Convex Coding
David Bradley, J. Andrew Bagnell

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

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

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

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

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

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

Bayesian Multitask Learning with Latent Hierarchies
Hal Daume

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

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

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

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

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

Approximate inference on planar graphs using Loop Calculus and Belief Propagation
Vicenç Gómez, Bert Kappen, Misha Chertkov

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

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

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

New inference strategies for solving Markov Decision Processes using reversible jump MCMC
Matt Hoffman, Hendrik Kueck, Nando de Freitas, Arnaud Doucet

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

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

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

MAP Estimation, Message Passing, and Perfect Graphs
Tony Jebara

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

Counting Belief Propagation
Kristian Kersting, Babak Ahmadi, Sriraam Natarajan

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

Constraint Processing in Lifted Probabilistic Inference
Jacek Kisynski, David Poole

The Temporal Logic of Causal Structures
Samantha Kleinberg, Bud Mishra

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

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

Improving Compressed Counting
Ping Li

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

Multi-Task Feature Learning Via Efficient L2,1-Norm Minimization
Jun Liu, Shuiwang Ji, Jieping Ye

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

Interpretation and Generalization of Score Matching
Siwei Lyu

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

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

Group Sparse Priors for Covariance Estimation
Benjamin Marlin, Mark Schmidt, Kevin Murphy

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

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

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

Using the Gene Ontology Hierarchy when Predicting Gene Function
Sara Mostafavi, Quaid Morris

Inference Algorithms and Matrix Representations for Probabilistic Conditional Independence
Mathias Niepert

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

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

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

A factorization criterion for acyclic directed mixed graphs
Thomas Richardson

Characterizing predictable classes of processes
Daniil Ryabko

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

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

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

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

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

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

Measuring Inconsistency in Probabilistic Knowledge Bases
Matthias Thimm

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

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

Probabilistic Structured Predictors
Shankar Vembu, Thomas Gärtner, Mario Boley

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

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

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

Herding Dynamic Weights for Partially Observed Random Field Models
Max Welling

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

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

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

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

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

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