Abstract is missing.
- Graphical Models for Bandit ProblemsKareem Amin, Michael Kearns, Umar Syed. 1-10 [doi]
- Extended Lifted Inference with Joint FormulasUdi Apsel, Ronen I. Brafman. 11-18 [doi]
- Learning is planning: near Bayes-optimal reinforcement learning via Monte-Carlo tree searchJohn Asmuth, Michael L. Littman. 19-26 [doi]
- Solving Cooperative Reliability GamesYoram Bachrach, Reshef Meir, Michal Feldman, Moshe Tennenholtz. 27-34 [doi]
- 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. 35-42 [doi]
- Semi-supervised Learning with Density Based DistancesAvleen Singh Bijral, Nathan D. Ratliff, Nathan Srebro. 43-50 [doi]
- Deconvolution of mixing time series on a graphAlexander W. Blocker, Edoardo Airoldi. 51-60 [doi]
- Factored Filtering of Continuous-Time SystemsE. Busra Celikkaya, Christian R. Shelton, William Lam. 61-68 [doi]
- Near-Optimal Target Learning With Stochastic Binary SignalsMithun Chakraborty, Sanmay Das, Malik Magdon-Ismail. 69-76 [doi]
- Filtered Fictitious Play for Perturbed Observation Potential Games and Decentralised POMDPsArchie C. Chapman, Simon A. Williamson, Nicholas R. Jennings. 77-85 [doi]
- A Framework for Optimizing Paper MatchingLaurent Charlin, Richard S. Zemel, Craig Boutilier. 86-95 [doi]
- A temporally abstracted Viterbi algorithmShaunak Chatterjee, Stuart Russell. 96-104 [doi]
- Smoothing Proximal Gradient Method for General Structured Sparse LearningXi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing. 105-114 [doi]
- EDML: A Method for Learning Parameters in Bayesian NetworksArthur Choi, Khaled S. Refaat, Adnan Darwiche. 115-124 [doi]
- Strictly Proper Mechanisms with Cooperating PlayersSangIn Chun, Ross D. Shachter. 125-134 [doi]
- A Logical Characterization of Constraint-Based Causal DiscoveryTom Claassen, Tom Heskes. 135-144 [doi]
- Ensembles of Kernel PredictorsCorinna Cortes, Mehryar Mohri, Afshin Rostamizadeh. 145-152 [doi]
- Bayesian network learning with cutting planesJames Cussens. 153-160 [doi]
- Active Learning for Developing Personalized TreatmentKun Deng, Joelle Pineau, Susan A. Murphy. 161-168 [doi]
- Efficient Optimal Learning for Contextual BanditsMiroslav Dudík, Daniel Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang 0001. 169-178 [doi]
- A Unifying Framework for Linearly Solvable ControlKrishnamurthy Dvijotham, Emanuel Todorov. 179-186 [doi]
- Boosting as a Product of ExpertsNarayanan Unny Edakunni, Gary Brown, Tim Kovacs. 187-194 [doi]
- PAC-Bayesian Policy Evaluation for Reinforcement LearningMahdi Milani Fard, Joelle Pineau, Csaba Szepesvári. 195-202 [doi]
- On the Complexity of Decision Making in Possibilistic Decision TreesHélène Fargier, Nahla Ben Amor, Wided Guezguez. 203-210 [doi]
- Inference in Probabilistic Logic Programs using Weighted CNF'sDaan Fierens, Guy Van den Broeck, Ingo Thon, Bernd Gutmann, Luc De Raedt. 211-220 [doi]
- Efficient Inference in Markov Control ProblemsThomas Furmston, David Barber. 221-229 [doi]
- Dynamic consistency and decision making under vacuous beliefPhan Hong Giang. 230-237 [doi]
- Hierarchical Affinity PropagationInmar E. Givoni, Clement Chung, Brendan J. Frey. 238-246 [doi]
- Approximation by QuantizationVibhav Gogate, Pedro Domingos. 247-255 [doi]
- Probabilistic Theorem ProvingVibhav Gogate, Pedro Domingos. 256-265 [doi]
- Generalized Fisher Score for Feature SelectionQuanquan Gu, Zhenhui Li, Jiawei Han. 266-273 [doi]
- Active Semi-Supervised Learning using Submodular FunctionsAndrew Guillory, Jeff Bilmes. 274-282 [doi]
- Bregman divergence as general framework to estimate unnormalized statistical modelsMichael Gutmann, Jun-ichiro Hirayama. 283-290 [doi]
- Reasoning about RoboCup Soccer NarrativesHannaneh Hajishirzi, Julia Hockenmaier, Erik T. Mueller, Eyal Amir. 291-300 [doi]
- Suboptimality Bounds for Stochastic Shortest Path ProblemsEric A. Hansen. 301-310 [doi]
- Sequential Inference for Latent Force ModelsJouni Hartikainen, Simo Särkkä. 311-318 [doi]
- What Cannot be Learned with Bethe ApproximationsUri Heinemann, Amir Globerson. 319-326 [doi]
- Portfolio Allocation for Bayesian OptimizationMatthew D. Hoffman, Eric Brochu, Nando de Freitas. 327-336 [doi]
- Sum-Product Networks: A New Deep ArchitectureHoifung Poon, Pedro Domingos. 337-346 [doi]
- Lipschitz Parametrization of Probabilistic Graphical ModelsJean Honorio. 347-354 [doi]
- Efficient Probabilistic Inference with Partial Ranking QueriesJonathan Huang, Ashish Kapoor, Carlos Guestrin. 355-362 [doi]
- Noisy-OR Models with Latent ConfoundingAntti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer. 363-372 [doi]
- Discovering causal structures in binary exclusive-or skew acyclic modelsTakanori Inazumi, Takashi Washio, Shohei Shimizu, Joe Suzuki, Akihiro Yamamoto, Yoshinobu Kawahara. 373-382 [doi]
- Detecting low-complexity unobserved causesDominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf. 383-391 [doi]
- Online Importance Weight Aware UpdatesNikos Karampatziakis, John Langford. 392-399 [doi]
- Modeling Social Networks with Node Attributes using the Multiplicative Attribute Graph ModelMyunghwan Kim 0002, Jure Leskovec. 400-409 [doi]
- Pitman-Yor Diffusion TreesDavid A. Knowles, Zoubin Ghahramani. 410-418 [doi]
- Learning Determinantal Point ProcessesAlex Kulesza, Ben Taskar. 419-427 [doi]
- Message-Passing Algorithms for Quadratic Programming Formulations of MAP EstimationAkshat Kumar, Shlomo Zilberstein. 428-435 [doi]
- An Efficient Protocol for Negotiation over Combinatorial Domains with Incomplete InformationMinyi Li, Quoc Bao Vo, Ryszard Kowalczyk. 436-444 [doi]
- Noisy Search with Comparative FeedbackShiau Hong Lim, Peter Auer. 445-452 [doi]
- Variational Algorithms for Marginal MAPQiang Liu, Alexander T. Ihler. 453-462 [doi]
- Classification of Sets using Restricted Boltzmann MachinesJérôme Louradour, Hugo Larochelle. 463-470 [doi]
- Belief change with noisy sensing in the situation calculusJianbing Ma, Weiru Liu, Paul Miller. 471-478 [doi]
- Improving the Scalability of Optimal Bayesian Network Learning with External-Memory Frontier Breadth-First Branch and Bound SearchBrandon M. Malone, Changhe Yuan, Eric A. Hansen, Susan Bridges. 479-488 [doi]
- Order-of-Magnitude Influence DiagramsRadu Marinescu, Nic Wilson. 489-496 [doi]
- Asymptotic Efficiency of Deterministic Estimators for Discrete Energy-Based Models: Ratio Matching and PseudolikelihoodBenjamin M. Marlin, Nando de Freitas. 497-505 [doi]
- Reconstructing Pompeian HouseholdsDavid M. Mimno. 506-513 [doi]
- Conditional Restricted Boltzmann Machines for Structured Output PredictionVolodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton. 514-522 [doi]
- Compact Mathematical Programs For DEC-MDPs With Structured Agent InteractionsHala Mostafa, Victor R. Lesser. 523-530 [doi]
- Fractional Moments on Bandit ProblemsAnanda Narayanan B., Balaraman Ravindran. 531-538 [doi]
- Dynamic Mechanism Design for Markets with Strategic ResourcesSwaprava Nath, Onno Zoeter, Yadati Narahari, Christopher R. Dance. 539-546 [doi]
- Multidimensional counting grids: Inferring word order from disordered bags of wordsNebojsa Jojic, Alessandro Perina. 547-556 [doi]
- Partial Order MCMC for Structure Discovery in Bayesian NetworksTeppo Niinimaki, Pekka Parviainen, Mikko Koivisto. 557-564 [doi]
- A Geometric Traversal Algorithm for Reward-Uncertain MDPsEunsoo Oh, Kee-Eung Kim. 565-572 [doi]
- Iterated risk measures for risk-sensitive Markov decision processes with discounted costTakayuki Osogami. 573-580 [doi]
- Price Updating in Combinatorial Prediction Markets with Bayesian NetworksDavid Pennock, Lirong Xia. 581-588 [doi]
- Identifiability of Causal Graphs using Functional ModelsJonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf. 589-598 [doi]
- Nonparametric Divergence Estimation with Applications to Machine Learning on DistributionsBarnabás Póczos, Liang Xiong, Jeff G. Schneider. 599-608 [doi]
- Compressed Inference for Probabilistic Sequential ModelsGungor Polatkan, Oncel Tuzel. 609-618 [doi]
- Fast MCMC sampling for Markov jump processes and continuous time Bayesian networksVinayak Rao, Yee Whye Teh. 619-626 [doi]
- New Probabilistic Bounds on Eigenvalues and Eigenvectors of Random Kernel MatricesNima Reyhani, Hideitsu Hino, Ricardo Vigário. 627-634 [doi]
- Learning with Missing FeaturesAfshin Rostamizadeh, Alekh Agarwal, Peter L. Bartlett. 635-642 [doi]
- Symbolic Dynamic Programming for Discrete and Continuous State MDPsScott Sanner, Karina Valdivia Delgado, Leliane Nunes de Barros. 643-652 [doi]
- Generalized Fast Approximate Energy Minimization via Graph Cuts: a-Expansion b-Shrink MovesMark W. Schmidt, Karteek Alahari. 653-660 [doi]
- An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal ModelsIlya Shpitser, Thomas S. Richardson, James M. Robins. 661-670 [doi]
- Graph Cuts is a Max-Product AlgorithmDaniel Tarlow, Inmar E. Givoni, Richard S. Zemel, Brendan J. Frey. 671-680 [doi]
- Adjustment Criteria in Causal Diagrams: An Algorithmic PerspectiveJohannes Textor, Maciej Liskiewicz. 681-688 [doi]
- Learning mixed graphical models from data with p larger than nInma Tur, Robert Castelo. 689-697 [doi]
- Robust learning Bayesian networks for prior beliefMaomi Ueno. 698-707 [doi]
- Distributed Anytime MAP InferenceJoop van de Ven, Fabio Ramos. 708-716 [doi]
- A Sequence of Relaxation Constraining Hidden Variable ModelsGreg Ver Steeg, Aram Galstyan. 717-726 [doi]
- The Structure of Signals: Causal Interdependence Models for Games of Incomplete InformationMichael P. Wellman, Lu Hong, Scott E. Page. 727-735 [doi]
- Generalised Wishart ProcessesAndrew Gordon Wilson, Zoubin Ghahramani. 736-744 [doi]
- Sparse matrix-variate Gaussian process blockmodels for network modelingFeng Yan, Zenglin Xu, Yuan (Alan) Qi. 745-752 [doi]
- Hierarchical Maximum Margin Learning for Multi-Class ClassificationJian-Bo Yang, Ivor W. Tsang. 753-760 [doi]
- Planar Cycle Covering GraphsJulian Yarkony, Alexander T. Ihler, Charless Fowlkes. 761-769 [doi]
- Tightening MRF Relaxations with Planar SubproblemsJulian Yarkony, Ragib Morshed, Alexander T. Ihler, Charless Fowlkes. 770-777 [doi]
- Rank/Norm Regularization with Closed-Form Solutions: Application to Subspace ClusteringYaoliang Yu, Dale Schuurmans. 778-785 [doi]
- Measuring the Hardness of Stochastic Sampling on Bayesian Networks with Deterministic Causalities: the k-TestHaohai Yu, Robert van Engelen. 786-795 [doi]
- Risk Bounds for Infinitely Divisible DistributionChao Zhang, Dacheng Tao. 796-803 [doi]
- Kernel-based Conditional Independence Test and Application in Causal DiscoveryKun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf. 804-813 [doi]
- Smoothing Multivariate Performance MeasuresXinhua Zhang, Ankan Saha, S. V. N. Vishwanathan. 814-821 [doi]
- Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU ParallelizationLu Zheng, Ole J. Mengshoel, Jike Chong. 822-830 [doi]
- Sparse Topical CodingJun Zhu, Eric P. Xing. 831-838 [doi]
- Testing whether linear equations are causal: A free probability theory approachJakob Zscheischler, Dominik Janzing, Kun Zhang. 839-846 [doi]
- Incentives in Group Decision-Making With Uncertainty and Subjective BeliefsRuggiero Cavallo. 849 [doi]
- Learning high-dimensional DAGs with latent and selection variables (Abstract)Diego Colombo, Marloes H. Maathuis, Markus Kalisch, Thomas S. Richardson. 850 [doi]
- Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs (Abstract)Alain Hauser, Peter Bühlmann. 851 [doi]
- Correction for Hidden Confounders in the Genetic Analysis of Gene Expression (Abstract)Jennifer Listgarten, Carl Myers Kadie, Eric E. Schadt, David Heckerman. 852 [doi]
- Statistical Mechanics of Semi-Supervised Clustering in Sparse Graphs (Abstract)Greg Ver Steeg, Aram Galstyan, Armen E. Allahverdyan. 853 [doi]