Google
Google Scholar
MS Academic
CiteSeerX
CORE
Semantic Scholar27. UAI 2011: Barcelona, Spain
- Fábio Gagliardi Cozman, Avi Pfeffer:
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
- Kareem Amin, Michael J. Kearns, Umar Syed:
Graphical Models for Bandit Problems. 1-10 - Udi Apsel, Ronen I. Brafman:
Extended Lifted Inference with Joint Formulas. 11-18 - 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 - Alexander W. Blocker, Edoardo M. Airoldi:
Deconvolution of mixing time series on a graph. 51-60 - 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 Andrew 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 - Shaunak Chatterjee, Stuart J. Russell:
A temporally abstracted Viterbi algorithm. 96-104 - 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 - SangIn Chun, Ross D. Shachter:
Strictly Proper Mechanisms with Cooperating Players. 125-134 - Tom Claassen, Tom Heskes:
A Logical Characterization of Constraint-Based Causal Discovery. 135-144 - Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh:
Ensembles of Kernel Predictors. 145-152 - 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 J. 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 - Narayanan Unny Edakunni, Gary Brown, Tim Kovacs:
Boosting as a Product of Experts. 187-194 - 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 - Thomas Furmston, David Barber:
Efficient Inference in Markov Control Problems. 221-229 - Phan Hong Giang:
Dynamic consistency and decision making under vacuous belief. 230-237 - Inmar E. Givoni, Clement Chung, Brendan J. Frey:
Hierarchical Affinity Propagation. 238-246 - Vibhav Gogate, Pedro M. Domingos:
Approximation by Quantization. 247-255 - Vibhav Gogate, Pedro M. Domingos:
Probabilistic Theorem Proving. 256-265 - Quanquan Gu, Zhenhui Li, Jiawei Han:
Generalized Fisher Score for Feature Selection. 266-273 - Andrew Guillory, Jeff A. Bilmes:
Active Semi-Supervised Learning using Submodular Functions. 274-282 - Michael Gutmann, Junichiro 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 - Jouni Hartikainen, Simo Särkkä:
Sequential Inference for Latent Force Models. 311-318 - Uri Heinemann, Amir Globerson:
What Cannot be Learned with Bethe Approximations. 319-326 - Matthew D. Hoffman, Eric Brochu, Nando de Freitas:
Portfolio Allocation for Bayesian Optimization. 327-336 - Hoifung Poon, Pedro M. Domingos:
Sum-Product Networks: A New Deep Architecture. 337-346 - 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 - Nikos Karampatziakis, John Langford:
Online Importance Weight Aware Updates. 392-399 - Myunghwan Kim, Jure Leskovec:
Modeling Social Networks with Node Attributes using the Multiplicative Attribute Graph Model. 400-409 - David A. Knowles, Zoubin Ghahramani:
Pitman-Yor Diffusion Trees. 410-418 - Alex Kulesza, Ben Taskar:
Learning Determinantal Point Processes. 419-427 - 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 - Shiau Hong Lim, Peter Auer:
Noisy Search with Comparative Feedback. 445-452 - Qiang Liu, Alexander T. Ihler:
Variational Algorithms for Marginal MAP. 453-462 - Jérôme Louradour, Hugo Larochelle:
Classification of Sets using Restricted Boltzmann Machines. 463-470 - Jianbing Ma, Weiru Liu, Paul C. 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 - Radu Marinescu, Nic Wilson:
Order-of-Magnitude Influence Diagrams. 489-496 - 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 - Ananda Narayanan B., Balaraman Ravindran:
Fractional Moments on Bandit Problems. 531-538 - 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 - Eunsoo Oh, Kee-Eung Kim:
A Geometric Traversal Algorithm for Reward-Uncertain MDPs. 565-572 - Takayuki Osogami:
Iterated risk measures for risk-sensitive Markov decision processes with discounted cost. 573-580 - David M. 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 - Gungor Polatkan, Oncel Tuzel:
Compressed Inference for Probabilistic Sequential Models. 609-618 - Vinayak A. 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 - Afshin Rostamizadeh, Alekh Agarwal, Peter L. Bartlett:
Learning with Missing Features. 635-642 - Scott Sanner, Karina Valdivia Delgado, Leliane Nunes de Barros:
Symbolic Dynamic Programming for Discrete and Continuous State MDPs. 643-652 - Mark 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 - Inma Tur, Robert Castelo:
Learning mixed graphical models from data with p larger than n. 689-697 - Maomi Ueno:
Robust learning Bayesian networks for prior belief. 698-707 - Joop van de Ven, Fabio Ramos:
Distributed Anytime MAP Inference. 708-716 - 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 - Andrew Gordon Wilson, Zoubin Ghahramani:
Generalised Wishart Processes. 736-744 - 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, Alexander T. Ihler, Charless C. Fowlkes:
Planar Cycle Covering Graphs. 761-769 - Julian Yarkony, Ragib Morshed, Alexander T. Ihler, Charless C. 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 - Chao Zhang, Dacheng Tao:
Risk Bounds for Infinitely Divisible Distribution. 796-803 - 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 - Jun Zhu, Eric P. Xing:
Sparse Topical Coding. 831-838 - 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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2020-05-29 22:33 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
the dblp computer science bibliography is funded by:
