27. UAI 2011: Barcelona, Spain
Fabio Gagliardi Cozman, Avi Pfeffer (Eds.): UAI 2011, Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial Intelligence, Barcelona, Spain, July 14-17, 2011. AUAI Press 2011 ISBN 978-0-9749039-7-2
Contributed Papers
- John Asmuth, Michael L. Littman: Learning is planning: near Bayes-optimal reinforcement learning via Monte-Carlo tree search. 19-26
- Yoram Bachrach, Reshef Meir, Michal Feldman, Moshe Tennenholtz: Solving Cooperative Reliability Games. 27-34
- Gowtham Bellala, Jason Stanley, Clayton Scott, Suresh K. Bhavnani: Active Diagnosis via AUC Maximization: An Efficient Approach for Multiple Fault Identification in Large Scale, Noisy Networks. 35-42
- Avleen Singh Bijral, Nathan D. Ratliff, Nathan Srebro: Semi-supervised Learning with Density Based Distances. 43-50
- E. Busra Celikkaya, Christian R. Shelton, William Lam: Factored Filtering of Continuous-Time Systems. 61-68
- Mithun Chakraborty, Sanmay Das, Malik Magdon-Ismail: Near-Optimal Target Learning With Stochastic Binary Signals. 69-76
- Archie C. Chapman, Simon A. Williamson, Nicholas R. Jennings: Filtered Fictitious Play for Perturbed Observation Potential Games and Decentralised POMDPs. 77-85
- Laurent Charlin, Richard S. Zemel, Craig Boutilier: A Framework for Optimizing Paper Matching. 86-95
- Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing: Smoothing Proximal Gradient Method for General Structured Sparse Learning. 105-114
- Arthur Choi, Khaled S. Refaat, Adnan Darwiche: EDML: A Method for Learning Parameters in Bayesian Networks. 115-124
- James Cussens: Bayesian network learning with cutting planes. 153-160
- Kun Deng, Joelle Pineau, Susan A. Murphy: Active Learning for Developing Personalized Treatment. 161-168
- Miroslav Dudík, Daniel Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang: Efficient Optimal Learning for Contextual Bandits. 169-178
- Krishnamurthy Dvijotham, Emanuel Todorov: A Unifying Framework for Linearly Solvable Control. 179-186
- Mahdi Milani Fard, Joelle Pineau, Csaba Szepesvári: PAC-Bayesian Policy Evaluation for Reinforcement Learning. 195-202
- Hélène Fargier, Nahla Ben Amor, Wided Guezguez: On the Complexity of Decision Making in Possibilistic Decision Trees. 203-210
- Daan Fierens, Guy Van den Broeck, Ingo Thon, Bernd Gutmann, Luc De Raedt: Inference in Probabilistic Logic Programs using Weighted CNF's. 211-220
- Phan Hong Giang: Dynamic consistency and decision making under vacuous belief. 230-237
- Michael Gutmann, Jun-ichiro Hirayama: Bregman divergence as general framework to estimate unnormalized statistical models. 283-290
- Hannaneh Hajishirzi, Julia Hockenmaier, Erik T. Mueller, Eyal Amir: Reasoning about RoboCup Soccer Narratives. 291-300
- Eric A. Hansen: Suboptimality Bounds for Stochastic Shortest Path Problems. 301-310
- Matthew D. Hoffman, Eric Brochu, Nando de Freitas: Portfolio Allocation for Bayesian Optimization. 327-336
- Jean Honorio: Lipschitz Parametrization of Probabilistic Graphical Models. 347-354
- Jonathan Huang, Ashish Kapoor, Carlos Guestrin: Efficient Probabilistic Inference with Partial Ranking Queries. 355-362
- Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer: Noisy-OR Models with Latent Confounding. 363-372
- Takanori Inazumi, Takashi Washio, Shohei Shimizu, Joe Suzuki, Akihiro Yamamoto, Yoshinobu Kawahara: Discovering causal structures in binary exclusive-or skew acyclic models. 373-382
- Dominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf: Detecting low-complexity unobserved causes. 383-391
- Myunghwan Kim, Jure Leskovec: Modeling Social Networks with Node Attributes using the Multiplicative Attribute Graph Model. 400-409
- Akshat Kumar, Shlomo Zilberstein: Message-Passing Algorithms for Quadratic Programming Formulations of MAP Estimation. 428-435
- Minyi Li, Quoc Bao Vo, Ryszard Kowalczyk: An Efficient Protocol for Negotiation over Combinatorial Domains with Incomplete Information. 436-444
- Jérôme Louradour, Hugo Larochelle: Classification of Sets using Restricted Boltzmann Machines. 463-470
- Jianbing Ma, Weiru Liu, Paul Miller: Belief change with noisy sensing in the situation calculus. 471-478
- Brandon M. Malone, Changhe Yuan, Eric A. Hansen, Susan Bridges: Improving the Scalability of Optimal Bayesian Network Learning with External-Memory Frontier Breadth-First Branch and Bound Search. 479-488
- Benjamin M. Marlin, Nando de Freitas: Asymptotic Efficiency of Deterministic Estimators for Discrete Energy-Based Models: Ratio Matching and Pseudolikelihood. 497-505
- David M. Mimno: Reconstructing Pompeian Households. 506-513
- Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton: Conditional Restricted Boltzmann Machines for Structured Output Prediction. 514-522
- Hala Mostafa, Victor R. Lesser: Compact Mathematical Programs For DEC-MDPs With Structured Agent Interactions. 523-530
- Swaprava Nath, Onno Zoeter, Yadati Narahari, Christopher R. Dance: Dynamic Mechanism Design for Markets with Strategic Resources. 539-546
- Nebojsa Jojic, Alessandro Perina: Multidimensional counting grids: Inferring word order from disordered bags of words. 547-556
- Teppo Niinimaki, Pekka Parviainen, Mikko Koivisto: Partial Order MCMC for Structure Discovery in Bayesian Networks. 557-564
- Takayuki Osogami: Iterated risk measures for risk-sensitive Markov decision processes with discounted cost. 573-580
- David Pennock, Lirong Xia: Price Updating in Combinatorial Prediction Markets with Bayesian Networks. 581-588
- Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf: Identifiability of Causal Graphs using Functional Models. 589-598
- Barnabás Póczos, Liang Xiong, Jeff G. Schneider: Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions. 599-608
- Vinayak Rao, Yee Whye Teh: Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks. 619-626
- Nima Reyhani, Hideitsu Hino, Ricardo Vigário: New Probabilistic Bounds on Eigenvalues and Eigenvectors of Random Kernel Matrices. 627-634
- Scott Sanner, Karina Valdivia Delgado, Leliane Nunes de Barros: Symbolic Dynamic Programming for Discrete and Continuous State MDPs. 643-652
- Mark W. Schmidt, Karteek Alahari: Generalized Fast Approximate Energy Minimization via Graph Cuts: a-Expansion b-Shrink Moves. 653-660
- Ilya Shpitser, Thomas S. Richardson, James M. Robins: An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal Models. 661-670
- Daniel Tarlow, Inmar E. Givoni, Richard S. Zemel, Brendan J. Frey: Graph Cuts is a Max-Product Algorithm. 671-680
- Johannes Textor, Maciej Liskiewicz: Adjustment Criteria in Causal Diagrams: An Algorithmic Perspective. 681-688
- Maomi Ueno: Robust learning Bayesian networks for prior belief. 698-707
- Greg Ver Steeg, Aram Galstyan: A Sequence of Relaxation Constraining Hidden Variable Models. 717-726
- Michael P. Wellman, Lu Hong, Scott E. Page: The Structure of Signals: Causal Interdependence Models for Games of Incomplete Information. 727-735
- Feng Yan, Zenglin Xu, Yuan (Alan) Qi: Sparse matrix-variate Gaussian process blockmodels for network modeling. 745-752
- Jian-Bo Yang, Ivor W. Tsang: Hierarchical Maximum Margin Learning for Multi-Class Classification. 753-760
- Julian Yarkony, Ragib Morshed, Alexander T. Ihler, Charless Fowlkes: Tightening MRF Relaxations with Planar Subproblems. 770-777
- Yaoliang Yu, Dale Schuurmans: Rank/Norm Regularization with Closed-Form Solutions: Application to Subspace Clustering. 778-785
- Haohai Yu, Robert van Engelen: Measuring the Hardness of Stochastic Sampling on Bayesian Networks with Deterministic Causalities: the k-Test. 786-795
- Kun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf: Kernel-based Conditional Independence Test and Application in Causal Discovery. 804-813
- Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan: Smoothing Multivariate Performance Measures. 814-821
- Lu Zheng, Ole J. Mengshoel, Jike Chong: Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization. 822-830
- Jakob Zscheischler, Dominik Janzing, Kun Zhang: Testing whether linear equations are causal: A free probability theory approach. 839-846
- Ruggiero Cavallo: Incentives in Group Decision-Making With Uncertainty and Subjective Beliefs. 849
Abstracts
- Diego Colombo, Marloes H. Maathuis, Markus Kalisch, Thomas S. Richardson: Learning high-dimensional DAGs with latent and selection variables (Abstract). 850
- Alain Hauser, Peter Bühlmann: Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs (Abstract). 851
- Jennifer Listgarten, Carl Myers Kadie, Eric E. Schadt, David Heckerman: Correction for Hidden Confounders in the Genetic Analysis of Gene Expression (Abstract). 852
- Greg Ver Steeg, Aram Galstyan, Armen E. Allahverdyan: Statistical Mechanics of Semi-Supervised Clustering in Sparse Graphs (Abstract). 853
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last updated on 2013-06-18T214307 by the dblp team