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Awards

  • Microsoft Best Paper Award: Sum-Product Networks: A New Deep Architecture, by Hoifung Poon and Pedro Domingos
  • Google Student Paper Award: Generalised Wishart Processes, by Andrew Wilson and Zoubin Ghahramani
  • Best Paper Runner-Up: A Sequence of Relaxation Constraining Hidden Variable Models, by Greg Ver Steeg and Aram Galstyan
  • Student Paper Runner-Up: Graph Cuts is a Max-Product Algorithm, by Daniel Tarlow, Inmar Givoni, Richard Zemel and Brendan Frey
  • Accepted Papers

    Title - Regular PapersAuthors
    Graphical Models for Bandit ProblemsKareem Amin, Michael Kearns, Umar Syed
    Extended Lifted Inference with Joint FormulasUdi Apsel, Ronen I. Brafman
    Learning is Planning: Near Bayes-optimal Reinforcement Learning via Monte-Carlo Tree SearchJohn Asmuth, Michael Littman
    Solving Cooperative Reliability GamesYoram Bachrach, Reshef Meir, Michal Feldman, Moshe Tennenholtz
    Active Diagnosis via AUC Maximization: An Efficient Approach for Multiple Fault Identification in Large Scale, Noisy NetworksGowtham Bellala, Jason Stanley, Clayton Scott, Suresh K. Bhavnani
    Semi-supervised Learning with Density Based DistancesAvleen S. Bijral, Nathan Ratliff, Nati Srebro
    Deconvolution of Mixing Time Series on a GraphAlexander W. Blocker, Edoardo M. Airoldi
    Factored Filtering of Continuous-Time SystemsE. Busra Celikkaya, Christian R. Shelton, William Lam
    Near-Optimal Target Learning With Stochastic Binary SignalsMithun Chakraborty, Sanmay Das, Malik Magdon-Ismail
    Filtered Fictitious Play for Perturbed Observation Potential Games and Decentralised POMDPsArchie C. Chapman, Simon A. Williamson, Nicholas R. Jennings
    A Framework for Optimizing Paper MatchingLaurent Charlin, Richard S. Zemel, Craig Boutilier
    A Temporally Abstracted Viterbi AlgorithmShaunak Chatterjee, Stuart Russell
    Smoothing Proximal Gradient Method for General Structured Sparse LearningXi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing
    EDML: A Method for Learning Parameters in Bayesian NetworksArthur Choi, Khaled S. Refaat, Adnan Darwiche
    Strictly Proper Mechanisms with Cooperating PlayersSangIn Chun, Ross D. Shachter
    A Logical Characterization of Constraint-Based Causal DiscoveryTom Claassen, Tom Heskes
    Ensembles of Kernel PredictorsCorinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
    Bayesian Network Learning with Cutting PlanesJames Cussens
    Active Learning for Developing Personalized TreatmentKun Deng, Joelle Pineau, Susan Murphy
    Efficient Optimal Learning for Contextual BanditsMiroslav Dudik, Daniel Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang
    A Unifying Framework for Linearly Solvable ControlKrishnamurthy Dvijotham, Emanuel Todorov
    Boosting as a Product of ExpertsNarayanan U. Edakunni, Gavin Brown, Tim Kovacs
    PAC-Bayesian Policy Evaluation for Reinforcement LearningMahdi Milani Fard, Joelle Pineau, Csaba Szepesvári
    On the Complexity of Decision Making in Possibilistic Decision TreesHélène Fargier, Nahla Ben Amor, Wided Guezguez
    Inference in Probabilistic Logic Programs using Weighted CNF'sDaan Fierens, Guy Van den Broeck, Ingo Thon, Bernd Gutmann, Luc De Raedt
    Efficient Inference in Markov Control ProblemsThomas Furmston, David Barber
    Dynamic Consistency and Decision Making under Vacuous BeliefPhan H. Giang
    Hierarchical Affinity PropagationInmar E. Givoni, Clement Chung, Brendan J. Frey
    Approximation by QuantizationVibhav Gogate, Pedro Domingos
    Probabilistic Theorem ProvingVibhav Gogate, Pedro Domingos
    Generalized Fisher Score for Feature SelectionQuanquan Gu, Zhenhui Li, Jiawei Han
    Active Semi-Supervised Learning using Submodular FunctionsAndrew Guillory, Jeff Bilmes
    Bregman Divergence as General Framework to Estimate Unnormalized Statistical ModelsMichael U. Gutmann, Jun-ichiro Hirayama
    Reasoning about RoboCup Soccer NarrativesHannaneh Hajishirzi, Julia Hockenmaier, Erik T. Mueller, Eyal Amir
    Suboptimality Bounds for Stochastic Shortest Path ProblemsEric A. Hansen
    Sequential Inference for Latent Force ModelsJouni Hartikainen, Simo Särkkä
    What Cannot be Learned with Bethe ApproximationsUri Heinemann, Amir Globerson
    Portfolio Allocation for Bayesian OptimizationMatthew Hoffman, Eric Brochu, Nando de Freitas
    Sum-Product Networks: A New Deep ArchitectureHoifung Poon, Pedro Domingos
    Lipschitz Parametrization of Probabilistic Graphical ModelsJean Honorio
    Efficient Probabilistic Inference with Partial Ranking QueriesJonathan Huang, Ashish Kapoor, Carlos Guestrin
    Noisy-OR Models with Latent ConfoundingAntti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
    Discovering Causal Structures in Binary Exclusive-or Skew Acyclic ModelsTakanori Inazumi, Takashi Washio, Shohei Shimizu, Joe Suzuki, Akihiro Yamamoto, Yoshinobu Kawahara
    Detecting Low-complexity Unobserved CausesDominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf
    Online Importance Weight Aware UpdatesNikos Karampatziakis, John Langford
    Modeling Social Networks with Node Attributes using the Multiplicative Attribute Graph ModelMyunghwan Kim, Jure Leskovec
    Pitman-Yor Diffusion TreesDavid A. Knowles, Zoubin Ghahramani
    Learning Determinantal Point ProcessesAlex Kulesza, Ben Taskar
    Message-Passing Algorithms for Quadratic Programming Formulations of MAP EstimationAkshat Kumar, Shlomo Zilberstein
    An Efficient Protocol for Negotiation over Combinatorial Domains with Incomplete InformationMinyi Li, Quoc Bao Vo, Ryszard Kowalczyk
    Noisy Search with Comparative FeedbackShiau Hong Lim, Peter Auer
    Variational Algorithms for Marginal MAPQiang Liu, Alexander T. Ihler
    Classification of Sets using Restricted Boltzmann MachinesJérôme Louradour, Hugo Larochelle
    Belief Change with Noisy Sensing in the Situation CalculusJianbing Ma, Weiru Liu, Paul Miller
    Improving the Scalability of Optimal Bayesian Network Learning with External-Memory Frontier Breadth-First Branch and Bound SearchBrandon Malone, Changhe Yuan, Eric A. Hansen, Susan Bridges
    Order-of-Magnitude Influence DiagramsRadu Marinescu, Nic Wilson
    Asymptotic Efficiency of Deterministic Estimators for Discrete Energy-Based Models: Ratio Matching and PseudolikelihoodBenjamin M. Marlin, Nando de Freitas
    Reconstructing Pompeian HouseholdsDavid Mimno
    Conditional Restricted Boltzmann Machines for Structured Output PredictionVolodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton
    Compact Mathematical Programs For DEC-MDPs With Structured Agent InteractionsHala Mostafa, Victor Lesser
    Fractional Moments on Bandit ProblemsAnanda Narayanan B, Balaraman Ravindran
    Dynamic Mechanism Design for Markets with Strategic ResourcesSwaprava Nath, Onno Zoeter, Yadati Narahari, Chris R. Dance
    Multidimensional counting grids: Inferring word order from disordered bags of wordsNebojsa Jojic, Alessandro Perina
    Partial Order MCMC for Structure Discovery in Bayesian NetworksTeppo Niinimäki, Pekka Parviainen, Mikko Koivisto
    A Geometric Traversal Algorithm for Reward-Uncertain MDPsEunsoo Oh, Kee-Eung Kim
    Iterated Risk Measures for Risk-sensitive Markov Decision Processes with Discounted CostTakayuki Osogami
    Price Updating in Combinatorial Prediction Markets with Bayesian NetworksDavid M. Pennock, Lirong Xia
    Identifiability of Causal Graphs using Functional ModelsJonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf
    Nonparametric Divergence Estimation with Applications to Machine Learning on DistributionsBarnabas Poczos, Liang Xiong, Jeff Schneider
    Compressed Inference for Probabilistic Sequential ModelsGungor Polatkan, Oncel Tuzel
    Fast MCMC Sampling for Markov Jump Processes and Continuous Time Bayesian NetworksVinayak Rao, Yee Whye Teh
    New Probabilistic Bounds on Eigenvalues and Eigenvectors of Random Kernel MatricesNima Reyhani, Hideitsu Hino, Ricardo Vigário
    Learning with Missing FeaturesAfshin Rostamizadeh, Alekh Agarwal, Peter Bartlett
    Symbolic Dynamic Programming for Discrete and Continuous State MDPsScott Sanner, Karina Valdivia Delgado, Leliane Nunes de Barros
    Generalized Fast Approximate Energy Minimization via Graph Cuts: α-Expansion β-Shrink MovesMark Schmidt, Karteek Alahari
    An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal ModelsIlya Shpitser, Thomas S. Richardson, James M. Robins
    Graph Cuts is a Max-Product AlgorithmDaniel Tarlow, Inmar E. Givoni, Richard S. Zemel, Brendan J. Frey
    Adjustment Criteria in Causal Diagrams: An Algorithmic PerspectiveJohannes Textor, Maciej Liśkiewicz
    Learning Mixed Graphical Models from Data with p larger than nInma Tur, Robert Castelo
    Robust Learning Bayesian Networks for Prior BeliefMaomi Ueno
    Distributed Anytime MAP InferenceJoop van de Ven, Fabio Ramos
    A Sequence of Relaxation Constraining Hidden Variable ModelsGreg Ver Steeg, Aram Galstyan
    The Structure of Signals: Causal Interdependence Models for Games of Incomplete InformationMichael P. Wellman, Lu Hong, Scott E. Page
    Generalised Wishart ProcessesAndrew Gordon Wilson, Zoubin Ghahramani
    Sparse Matrix-variate Gaussian Process Blockmodels for Network ModelingFeng Yan, Zenglin Xu, Yuan (Alan) Qi
    Hierarchical Maximum Margin Learning for Multi-Class ClassificationJian-Bo Yang , Ivor W. Tsang
    Planar Cycle Covering GraphsJulian Yarkony, Alexander T. Ihler, Charless C. Fowlkes
    Tightening MRF Relaxations with Planar SubproblemsJulian Yarkony, Ragib Morshed, Alexander T. Ihler, Charless C. Fowlkes
    Rank/Norm Regularization with Closed-Form Solutions: Application to Subspace ClusteringYao-Liang Yu, Dale Schuurmans
    Measuring the Hardness of Stochastic Sampling on Bayesian Networks with Deterministic Causalities: the k-TestHaohai Yu, Robert van Engelen
    Risk Bounds for Infinitely Divisible DistributionChao Zhang, Dacheng Tao
    Kernel-based Conditional Independence Test and Application in Causal DiscoveryKun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf
    Smoothing Multivariate Performance MeasuresXinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
    Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU ParallelizationLu Zheng, Ole Mengshoel, Jike Chong
    Sparse Topical CodingJun Zhu, Eric P. Xing
    Testing whether linear equations are causal: A free probability theory approachJakob Zscheischler, Dominik Janzing, Kun Zhang
    Title - Extended AbstractsAuthors
    Incentives in Group Decision-Making With Uncertainty and Subjective BeliefsRuggiero Cavallo
    Learning high-dimensional DAGs with latent and selection variablesDiego Colombo, Marloes H. Maathuis, Markus Kalisch, Thomas S. Richardson
    Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs (Abstract)Alain Hauser, Peter Bühlmann
    Correction for Hidden Confounders in the Genetic Analysis of Gene ExpressionJennifer Listgarten, Carl Kadie, Eric E. Schadt, David Heckerman
    Statistical Mechanics of Semi-Supervised Clustering in Sparse GraphsGreg Ver Steeg, Aram Galstyan, Armen Allahverdyan