| Title - Regular Papers | Authors |
| Graphical Models for Bandit Problems | Kareem Amin, Michael Kearns, Umar Syed |
| Extended Lifted Inference with Joint Formulas | Udi Apsel, Ronen I. Brafman |
| Learning is Planning: Near Bayes-optimal Reinforcement Learning via Monte-Carlo Tree Search | John Asmuth, Michael Littman |
| Solving Cooperative Reliability Games | Yoram Bachrach, Reshef Meir, Michal Feldman, Moshe Tennenholtz |
| Active Diagnosis via AUC Maximization: An Efficient Approach for Multiple Fault Identification in Large Scale, Noisy Networks | Gowtham Bellala, Jason Stanley, Clayton Scott, Suresh K. Bhavnani |
| Semi-supervised Learning with Density Based Distances | Avleen S. Bijral, Nathan Ratliff, Nati Srebro |
| Deconvolution of Mixing Time Series on a Graph | Alexander W. Blocker, Edoardo M. Airoldi |
| Factored Filtering of Continuous-Time Systems | E. Busra Celikkaya, Christian R. Shelton, William Lam |
| Near-Optimal Target Learning With Stochastic Binary Signals | Mithun Chakraborty, Sanmay Das, Malik Magdon-Ismail |
| Filtered Fictitious Play for Perturbed Observation Potential Games and Decentralised POMDPs | Archie C. Chapman, Simon A. Williamson, Nicholas R. Jennings |
| A Framework for Optimizing Paper Matching | Laurent Charlin, Richard S. Zemel, Craig Boutilier |
| A Temporally Abstracted Viterbi Algorithm | Shaunak Chatterjee, Stuart Russell |
| Smoothing Proximal Gradient Method for General Structured Sparse Learning | Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing |
| EDML: A Method for Learning Parameters in Bayesian Networks | Arthur Choi, Khaled S. Refaat, Adnan Darwiche |
| Strictly Proper Mechanisms with Cooperating Players | SangIn Chun, Ross D. Shachter |
| A Logical Characterization of Constraint-Based Causal Discovery | Tom Claassen, Tom Heskes |
| Ensembles of Kernel Predictors | Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh |
| Bayesian Network Learning with Cutting Planes | James Cussens |
| Active Learning for Developing Personalized Treatment | Kun Deng, Joelle Pineau, Susan Murphy |
| Efficient Optimal Learning for Contextual Bandits | Miroslav Dudik, Daniel Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang |
| A Unifying Framework for Linearly Solvable Control | Krishnamurthy Dvijotham, Emanuel Todorov |
| Boosting as a Product of Experts | Narayanan U. Edakunni, Gavin Brown, Tim Kovacs |
| PAC-Bayesian Policy Evaluation for Reinforcement Learning | Mahdi Milani Fard, Joelle Pineau, Csaba Szepesvári |
| On the Complexity of Decision Making in Possibilistic Decision Trees | Hélène Fargier, Nahla Ben Amor, Wided Guezguez |
| Inference in Probabilistic Logic Programs using Weighted CNF's | Daan Fierens, Guy Van den Broeck, Ingo Thon, Bernd Gutmann, Luc De Raedt |
| Efficient Inference in Markov Control Problems | Thomas Furmston, David Barber |
| Dynamic Consistency and Decision Making under Vacuous Belief | Phan H. Giang |
| Hierarchical Affinity Propagation | Inmar E. Givoni, Clement Chung, Brendan J. Frey |
| Approximation by Quantization | Vibhav Gogate, Pedro Domingos |
| Probabilistic Theorem Proving | Vibhav Gogate, Pedro Domingos |
| Generalized Fisher Score for Feature Selection | Quanquan Gu, Zhenhui Li, Jiawei Han |
| Active Semi-Supervised Learning using Submodular Functions | Andrew Guillory, Jeff Bilmes |
| Bregman Divergence as General Framework to Estimate Unnormalized Statistical Models | Michael U. Gutmann, Jun-ichiro Hirayama |
| Reasoning about RoboCup Soccer Narratives | Hannaneh Hajishirzi, Julia Hockenmaier, Erik T. Mueller, Eyal Amir |
| Suboptimality Bounds for Stochastic Shortest Path Problems | Eric A. Hansen |
| Sequential Inference for Latent Force Models | Jouni Hartikainen, Simo Särkkä |
| What Cannot be Learned with Bethe Approximations | Uri Heinemann, Amir Globerson |
| Portfolio Allocation for Bayesian Optimization | Matthew Hoffman, Eric Brochu, Nando de Freitas |
| Sum-Product Networks: A New Deep Architecture | Hoifung Poon, Pedro Domingos |
| Lipschitz Parametrization of Probabilistic Graphical Models | Jean Honorio |
| Efficient Probabilistic Inference with Partial Ranking Queries | Jonathan Huang, Ashish Kapoor, Carlos Guestrin |
| Noisy-OR Models with Latent Confounding | Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer |
| Discovering Causal Structures in Binary Exclusive-or Skew Acyclic Models | Takanori Inazumi, Takashi Washio, Shohei Shimizu, Joe Suzuki, Akihiro Yamamoto, Yoshinobu Kawahara |
| Detecting Low-complexity Unobserved Causes | Dominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf |
| Online Importance Weight Aware Updates | Nikos Karampatziakis, John Langford |
| Modeling Social Networks with Node Attributes using the Multiplicative Attribute Graph Model | Myunghwan Kim, Jure Leskovec |
| Pitman-Yor Diffusion Trees | David A. Knowles, Zoubin Ghahramani |
| Learning Determinantal Point Processes | Alex Kulesza, Ben Taskar |
| Message-Passing Algorithms for Quadratic Programming Formulations of MAP Estimation | Akshat Kumar, Shlomo Zilberstein |
| An Efficient Protocol for Negotiation over Combinatorial Domains with Incomplete Information | Minyi Li, Quoc Bao Vo, Ryszard Kowalczyk |
| Noisy Search with Comparative Feedback | Shiau Hong Lim, Peter Auer |
| Variational Algorithms for Marginal MAP | Qiang Liu, Alexander T. Ihler |
| Classification of Sets using Restricted Boltzmann Machines | Jérôme Louradour, Hugo Larochelle |
| Belief Change with Noisy Sensing in the Situation Calculus | Jianbing Ma, Weiru Liu, Paul Miller |
| Improving the Scalability of Optimal Bayesian Network Learning with External-Memory Frontier Breadth-First Branch and Bound Search | Brandon Malone, Changhe Yuan, Eric A. Hansen, Susan Bridges |
| Order-of-Magnitude Influence Diagrams | Radu Marinescu, Nic Wilson |
| Asymptotic Efficiency of Deterministic Estimators for Discrete Energy-Based Models: Ratio Matching and Pseudolikelihood | Benjamin M. Marlin, Nando de Freitas |
| Reconstructing Pompeian Households | David Mimno |
| Conditional Restricted Boltzmann Machines for Structured Output Prediction | Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton |
| Compact Mathematical Programs For DEC-MDPs With Structured Agent Interactions | Hala Mostafa, Victor Lesser |
| Fractional Moments on Bandit Problems | Ananda Narayanan B, Balaraman Ravindran |
| Dynamic Mechanism Design for Markets with Strategic Resources | Swaprava Nath, Onno Zoeter, Yadati Narahari, Chris R. Dance |
| Multidimensional counting grids: Inferring word order from disordered bags of words | Nebojsa Jojic, Alessandro Perina |
| Partial Order MCMC for Structure Discovery in Bayesian Networks | Teppo Niinimäki, Pekka Parviainen, Mikko Koivisto |
| A Geometric Traversal Algorithm for Reward-Uncertain MDPs | Eunsoo Oh, Kee-Eung Kim |
| Iterated Risk Measures for Risk-sensitive Markov Decision Processes with Discounted Cost | Takayuki Osogami |
| Price Updating in Combinatorial Prediction Markets with Bayesian Networks | David M. Pennock, Lirong Xia |
| Identifiability of Causal Graphs using Functional Models | Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf |
| Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions | Barnabas Poczos, Liang Xiong, Jeff Schneider |
| Compressed Inference for Probabilistic Sequential Models | Gungor Polatkan, Oncel Tuzel |
| Fast MCMC Sampling for Markov Jump Processes and Continuous Time Bayesian Networks | Vinayak Rao, Yee Whye Teh |
| New Probabilistic Bounds on Eigenvalues and Eigenvectors of Random Kernel Matrices | Nima Reyhani, Hideitsu Hino, Ricardo Vigário |
| Learning with Missing Features | Afshin Rostamizadeh, Alekh Agarwal, Peter Bartlett |
| Symbolic Dynamic Programming for Discrete and Continuous State MDPs | Scott Sanner, Karina Valdivia Delgado, Leliane Nunes de Barros |
| Generalized Fast Approximate Energy Minimization via Graph Cuts: α-Expansion β-Shrink Moves | Mark Schmidt, Karteek Alahari |
| An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal Models | Ilya Shpitser, Thomas S. Richardson, James M. Robins |
| Graph Cuts is a Max-Product Algorithm | Daniel Tarlow, Inmar E. Givoni, Richard S. Zemel, Brendan J. Frey |
| Adjustment Criteria in Causal Diagrams: An Algorithmic Perspective | Johannes Textor, Maciej Liśkiewicz |
| Learning Mixed Graphical Models from Data with p larger than n | Inma Tur, Robert Castelo |
| Robust Learning Bayesian Networks for Prior Belief | Maomi Ueno |
| Distributed Anytime MAP Inference | Joop van de Ven, Fabio Ramos |
| A Sequence of Relaxation Constraining Hidden Variable Models | Greg Ver Steeg, Aram Galstyan |
| The Structure of Signals: Causal Interdependence Models for Games of Incomplete Information | Michael P. Wellman, Lu Hong, Scott E. Page |
| Generalised Wishart Processes | Andrew Gordon Wilson, Zoubin Ghahramani |
| Sparse Matrix-variate Gaussian Process Blockmodels for Network Modeling | Feng Yan, Zenglin Xu, Yuan (Alan) Qi |
| Hierarchical Maximum Margin Learning for Multi-Class Classification | Jian-Bo Yang , Ivor W. Tsang |
| Planar Cycle Covering Graphs | Julian Yarkony, Alexander T. Ihler, Charless C. Fowlkes |
| Tightening MRF Relaxations with Planar Subproblems | Julian Yarkony, Ragib Morshed, Alexander T. Ihler, Charless C. Fowlkes |
| Rank/Norm Regularization with Closed-Form Solutions: Application to Subspace Clustering | Yao-Liang Yu, Dale Schuurmans |
| Measuring the Hardness of Stochastic Sampling on Bayesian Networks with Deterministic Causalities: the k-Test | Haohai Yu, Robert van Engelen |
| Risk Bounds for Infinitely Divisible Distribution | Chao Zhang, Dacheng Tao |
| Kernel-based Conditional Independence Test and Application in Causal Discovery | Kun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf |
| Smoothing Multivariate Performance Measures | Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan |
| Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization | Lu Zheng, Ole Mengshoel, Jike Chong |
| Sparse Topical Coding | Jun Zhu, Eric P. Xing |
| Testing whether linear equations are causal: A free probability theory approach | Jakob Zscheischler, Dominik Janzing, Kun Zhang |
