Accepted papers
A BAYESIAN PROBABILITY CALCULUS FOR DENSITY MATRICES
Manfred Warmuth and Dima Kuzmin
A COMPACT, HIERARCHICAL Q-FUNCTION DECOMPOSITION
Bhaskara Marthi, Stuart Russell and David Andre
A CONCENTRATION THEOREM FOR PROJECTIONS
Sanjoy Dasgupta, Daniel Hsu and Nakul Verma
A NEW AXIOMATIZATION FOR LIKELIHOOD GAMBLES
Phan Giang
A NON-PARAMETRIC BAYESIAN METHOD FOR INFERRING HIDDEN CAUSES
Frank Wood, Thomas L. Griffiths and Zoubin Ghahramani
A SELF-SUPERVISED TERRAIN ROUGHNESS ESTIMATOR FOR OFF-ROAD AUTONOMOUS DRIVING
David Stavens and Sebastian Thrun
A SIMPLE APPROACH FOR FINDING THE GLOBALLY OPTIMAL BAYESIAN NETWORK STRUCTURE
Tomi Silander and Petri Myllymäki
A THEORETICAL STUDY OF Y STRUCTURES FOR CAUSAL DISCOVERY
Subramani Mani, Gregory Cooper and Peter Spirtes
A VARIATIONAL APPROACH FOR APPROXIMATING BAYESIAN NETWORKS BY EDGE DELETION
Arthur Choi and Adnan Darwiche
ADJACENCY-FAITHFULNESS AND CONSERVATIVE CAUSAL INFERENCE
Joseph Ramsey, Jiji Zhang and Peter Spirtes
ADVANCES IN EXACT BAYESIAN STRUCTURE DISCOVERY IN BAYESIAN NETWORKS
Mikko Koivisto
AN EFFICIENT OPTIMAL-EQUILIBRIUM ALGORITHM FOR TWO-PLAYER GAME TREES
Michael Littman, Nishkam Ravi, Arjun Talwar and Martin Zinkevich
AN EFFICIENT TRIPLET-BASED ALGORITHM FOR EVIDENTIAL REASONING
Yaxin Bi and Jiwen Guan
AN EMPIRICAL COMPARISON OF ALGORITHMS FOR AGGREGATING EXPERT PREDICTIONS
Varsha Dani, Omid Madani, David Pennock, Sumit Sanghai and Brian Galebach
APPROXIMATE SEPARABILITY FOR WEAK INTERACTION IN DYNAMIC SYSTEMS
Avi Pfeffer
ASYMMETRIC SEPARATION FOR LOCAL INDEPENDENCE GRAPHS
Vanessa Didelez
AXIOMATIC FOUNDATIONS FOR A CLASS OF GENERALIZED EXPECTED UTILITY: ALGEBRAIC EXPECTED UTILITY
Paul Weng
BAYESIAN INFERENCE FOR GAUSSIAN MIXED GRAPH MODELS
Ricardo Silva and Zoubin Ghahramani
BAYESIAN MULTICATEGORY SUPPORT VECTOR MACHINES
Zhihua Zhang and Michael I. Jordan
BAYESIAN RANDOM FIELDS: THE BETHE-LAPLACE APPROXIMATION
Max Welling and Sridevi Parise
BELIEF UPDATE IN CLG BAYESIAN NETWORKS WITH LAZY PROPAGATION
Anders Madsen
CHI-SQUARE TESTS DRIVEN METHOD FOR LEARNING THE STRUCTURE OF FACTORED MDPS
Thomas Degris, Olivier Sigaud and Pierre-Henri Wuillemin
CONTINUOUS TIME MARKOV NETWORKS
Tal El-Hay, Nir Friedman, Daphne Koller and Raz Kupferman
CONVEX STRUCTURE LEARNING FOR BAYESIAN NETWORKS: POLYNOMIAL FEATURE SELECTION AND APPROXIMATE ORDERING
Yuhong Guo and Dale Schuurmans
CUTSET SAMPLING WITH LIKELIHOOD WEIGHTING
Bozhena Bidyuk and Rina Dechter
DIMENSION REDUCTION IN SINGULARLY PERTURBED CONTINUOUS-TIME BAYESIAN NETWORKS
Nir Friedman and Raz Kupferman
DIRECT AND INDIRECT EFFECTS OF SEQUENTIAL TREATMENTS
Vanessa Didelez, A. Philip Dawid and Sara Geneletti
DISCRIMINATIVE LEARNING VIA SEMIDEFINITE PROBABILISTIC MODELS
Koby Crammer and Amir Globerson
EFFICIENT SELECTION OF DISAMBIGUATING ACTIONS FOR STEREO VISION
Monika Schaeffer and Ronald Parr
FASTER GAUSSIAN SUMMATION: THEORY AND EXPERIMENT
Dongryeol Lee and Alexander Gray
FITTING GRAPHICAL INTERACTION MODELS TO MULTIVARIATE TIME SERIES
Michael Eichler
FROM INFLUENCE DIAGRAMS TO MULTI-OPERATOR CLUSTER DAGS
Cedric Pralet, Thomas Schiex and Gerard Verfaillie
GENE EXPRESSION TIME COURSE CLUSTERING WITH COUNTABLY INFINITE HIDDEN MARKOV MODELS
Matthew Beal and Praveen Krishnamurthy
GENERAL-PURPOSE MCMC INFERENCE OVER RELATIONAL STRUCTURES
Brian Milch and Stuart Russell
GIBBS SAMPLING FOR (COUPLED) INFINITE MIXTURE MODELS IN THE STICK BREAKING REPRESENTATION
Ian Porteous, Alex Ihler, Padhriac Smyth and Max Welling
GRAPHICAL CONDITION FOR IDENTIFICATION IN RECURSIVE SEM
Carlos Brito and Judea Pearl
IDENTIFICATION OF CONDITIONAL INTERVENTIONAL DISTRIBUTIONS
Ilya Shpitser and Judea Pearl
IDENTIFYING THE RELEVANT NODES WITHOUT LEARNING THE MODEL
Jose M. Peña, Roland Nilsson, Johan Björkegren and Jesper Tegnér
INCREMENTAL MODEL-BASED LEARNERS WITH FORMAL LEARNING-TIME GUARANTEES
Alexander L. Strehl, Lihong Li and Michael L. Littman
INEQUALITY CONSTRAINTS IN CAUSAL MODELS WITH HIDDEN VARIABLES
Changsung Kang and Jin Tian
INFERENCE IN HYBRID BAYESIAN NETWORKS USING MIXTURES OF GAUSSIANS
Prakash Shenoy
INFINITE HIDDEN RELATIONAL MODELS
Zhao Xu, Volker Tresp, Kai Yu and Hans-Peter Kriegel
LINEAR ALGEBRA APPROACH TO SEPARABLE BAYESIAN NETWORKS
Chalee Asavathiratham
MAIES: A TOOL FOR DNA MIXTURE ANALYSIS
Robert Cowell, Steffen Lauritzen and Julia Mortera
MATRIX TILE ANALYSIS
Inmar Givoni, Vincent Cheung and Brendan Frey
MCMC FOR DOUBLY-INTRACTABLE DISTRIBUTIONS
Iain Murray, Zoubin Ghahramani and David MacKay
METHODS FOR COMPUTING STATE SIMILARITY IN MARKOV DECISION PROCESSES
Norman Francis Ferns, Pablo Samuel Castro, Doina Precup and Prakash Panangaden
NON-MINIMAL TRIANGULATIONS FOR MIXED STOCHASTIC/DETERMINISTIC GRAPHICAL MODELS
Chris Bartels and Jeff Bilmes
ON THE NUMBER OF SAMPLES NEEDED TO LEARN THE CORRECT STRUCTURE OF A BAYESIAN NETWORK
Or Zuk, Shiri Margel and Eytan Domany
ON THE ROBUSTNESS OF MOST PROBABLE EXPLANATIONS
Hei Chan and Adnan Darwiche
OPTIMAL COORDINATED PLANNING AMONGST SELF-INTERESTED AGENTS WITH PRIVATE STATE
Ruggiero Cavallo, David Parkes and Satinder Singh
PEARL'S CALCULUS OF INTERVENTION IS COMPLETE
Yimin Huang and Marco Valtorta
PRACTICAL LINEAR VALUE-APPROXIMATION TECHNIQUES FOR FIRST-ORDER MDPS
Scott Sanner and Craig Boutilier
PREDICTING CONDITIONAL QUANTILES VIA REDUCTION TO CLASSIFICATION
John Langford, Roberto Oliveira and Bianca Zadrozny
PROPAGATION OF DELAYS IN THE NATIONAL AIRSPACE SYSTEM
Kathryn Laskey, Ning Xu and Chun-Hung Chen
RANKING BY DEPENDENCE--A FAIR CRITERIA
Harald Steck
REASONING ABOUT UNCERTAINTY IN METRIC SPACES
Seunghwan Lee
RECOGNIZING ACTIVITIES AND SPATIAL CONTEXT USING WEARABLE SENSORS
Amarnag Subramanya, Alvin Raj, Jeff Bilmes and Dieter Fox
RESIDUAL BELIEF PROPAGATION: INFORMED SCHEDULING FOR ASYNCHRONOUS MESSAGE PASSING
Gal Elidan, Ian McGraw and Daphne Koller
ROBUST LEARNING EQUILIBRIUM
Itai Ashlagi, Dov Monderer and Moshe Tennenholtz
SENSITIVITY ANALYSIS FOR THRESHOLD DECISION MAKING WITH DYNAMIC NETWORKS
Theodore Charitos and Linda C. van der Gaag
SEQUENTIAL DOCUMENT REPRESENTATIONS AND SIMPLICIAL CURVES
Guy Lebanon
STOCHASTIC OPTIMAL CONTROL IN CONTINUOUS SPACE-TIME MULTI-AGENT SYSTEMS
Wim Wiegerinck, Bart van den Broek and Bert Kappen
STRATIFIED ANALYSIS OF "PROBABILITIES OF CAUSATION"
Manabu Kuroki and Zhihong Cai
STRUCTURED PRIORS FOR STRUCTURE LEARNING
Vikash Mansinghka, Charles Kemp, Thomas Griffiths and Joshua Tenenbaum
THE AI&M PROCEDURE FOR LEARNING FROM INCOMPLETE DATA
Manfred Jaeger
VARIABLE NOISE AND DIMENSIONALITY REDUCTION FOR SPARSE GAUSSIAN PROCESSES
Edward Snelson and Zoubin Ghahramani
VISUALIZATION OF COLLABORATIVE DATA
Guobiao Mei and Christian Shelton
