- On Maximum a Posteriori Estimation of Hidden Markov Processes
- Armen Allahverdyan, Aram Galstyan
- Lower Bound Bayesian Networks - Efficient Inference of Lower Bounds on Probability Distributions
- Daniel Andrade, Bernhard Sick
- On Smoothing and Inference for Topic Models
- Arthur Asuncion, Max Welling, Padhraic Smyth, Yee Whye Teh
- REGAL: A Regularization based Algorithm for Reinforcement Learning in Weakly Communicating MDPs
- Peter Bartlett, Ambuj Tewari
- Alternating Projections for Learning with Expectation Constraints
- Kedar Bellare, Gregory Druck, Andrew McCallum
- Conditional Probability Tree Estimation Analysis and Algorithms
- Alina Beygelzimer, John Langford, Yury Lifshits, Gregory Sorkin, Alex Strehl
- Deterministic POMDPs Revisited
- Blai Bonet
- Optimization of Structured Mean Field Objectives
- Alexandre Bouchard-Côté, Mike Jordan
- Multilingual Topic Models for Unaligned Text
- Jordan Boyd-Graber, David Blei
- Convex Coding
- David Bradley, J. Andrew Bagnell
- Temporal Difference Networks for Dynamical Systems with Continuous Observations and Actions
- Vigorito Christopher
- Mean Field Variational Approximation for Continuous-Time Bayesian Networks
- Ido Cohn, Tal El-hay, Nir Friedman, Raz Kupferman
- Prediction Markets, Mechanism Design, and Cooperative Game Theory
- Vincent Conitzer
- L_2 Regularization for Learning Kernels
- Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
- Complexity Analysis and Variational Inference for Interpretation-based Probabilistic Description Logic
- Fabio Cozman, Rodrigo Polastro
- Seeing the Forest Despite the Trees: Large Scale Spatial-Temporal Decision Making
- Mark Crowley, David Poole, John Nelson
- Bayesian Multitask Learning with Latent Hierarchies
- Hal Daume
- Correlated Non-Parametric Latent Feature Models
- Finale Doshi-Velez, Zoubin Ghahramani
- A Sampling-Based Approach to Computing Equilibria in Succinct Extensive-Form Games
- Miroslav Dudik, Geoffrey Gordon
- Learning Continuous-Time Social Network Dynamics
- Yu Fan, Christian Shelton
- Robust Graphical Modelling with t-Distributions
- Michael Finegold, Mathias Drton
- Generating Optimal Plans in Highly-Dynamic Domains
- Christian Fritz, Sheila McIlraith
- Approximate inference on planar graphs using Loop Calculus and Belief Propagation
- Vicenç Gómez, Bert Kappen, Misha Chertkov
- Censored Exploration and the Dark Pool Problem
- Kuzman Ganchev, Michael Kearns, Yuriy Nevmyvaka, Jennifer Wortman
- Distributed Parallel Inference on Large Factor Graphs
- Joseph Gonzalez, Yucheng Low, Carlos Guestrin, David O'Hallaron
- First-Order Mixed Integer Linear Programming
- Geoffrey Gordon, Sue Ann Hong, Miroslav Dudik
- New inference strategies for solving Markov Decision Processes using reversible jump MCMC
- Matt Hoffman, Hendrik Kueck, Nando de Freitas, Arnaud Doucet
- Improved Mean and Variance Approximations for Belief Net Response via Network Doubling
- Peter Hooper, Yasin Abbasi-Yadkori, Bret Hoehn, Russell Greiner
- Bayesian Discovery of Linear Acyclic Causal Models
- Patrik Hoyer, Antti Hyttinen
- Identifying confounders using additive noise models
- Dominik Janzing, Jonas Peters, Joris Mooij, Bernhard Schoelkopf
- MAP Estimation, Message Passing, and Perfect Graphs
- Tony Jebara
- Temporal Action-Graph Games: A New Representation for Dynamic Games
- Albert Xin Jiang, Kevin Leyton-Brown, Avi Pfeffer
- Counting Belief Propagation
- Kristian Kersting, Babak Ahmadi, Sriraam Natarajan
- Monolingual Probabilistic Programming Using Generalized Coroutines
- Oleg Kiselyov, Chung-chieh Shan
- Constraint Processing in Lifted Probabilistic Inference
- Jacek Kisynski, David Poole
- The Temporal Logic of Causal Structures
- Samantha Kleinberg, Bud Mishra
- MAP Estimation of Semi-Metric MRFs via Hierarchical Graph Cuts
- M. Pawan Kumar, Daphne Koller
- Quantum Annealing for Clustering
- Kenichi Kurihara, Shu Tanaka, Seiji Miyashita
- Improving Compressed Counting
- Ping Li
- A Bayesian Sampling Approach to Exploration in Reinforcement Learning
- Michael Littman, Lihong Li, Ali Nouri, David Wingate, John Asmuth
- Multi-Task Feature Learning Via Efficient L2,1-Norm Minimization
- Jun Liu, Shuiwang Ji, Jieping Ye
- Quantifying the Strategyproofness of Mechanisms via Metrics on Payoff Distributions
- Benjamin Lubin, David Parkes
- Interpretation and Generalization of Score Matching
- Siwei Lyu
- Multiple Source Adaptation and the Renyi Divergence
- Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
- Domain Knowledge Uncertainty and Probabilistic Parameter Constraints
- Yi Mao, Guy Lebanon
- Group Sparse Priors for Covariance Estimation
- Benjamin Marlin, Mark Schmidt, Kevin Murphy
- Convergent message passing algorithms - a unifying view
- Talya Meltzer, Amir Globerson, Yair Weiss
- Convexifying the Bethe Free Energy
- Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman
- Virtual Vector Machine for Bayesian Online Classification
- Thomas Minka, Rongjing Xiang, Alan Qi
- Using the Gene Ontology Hierarchy when Predicting Gene Function
- Sara Mostafavi, Quaid Morris
- Inference Algorithms and Matrix Representations for Probabilistic Conditional Independence
- Mathias Niepert
- Exact Structure Discovery in Bayesian Networks with Less Space
- Pekka Parviainen, Mikko Koivisto
- Regret-based Reward Elicitation for Markov Decision Processes
- Kevin Regan, Craig Boutilier
- BPR: Bayesian Personalized Ranking from Implicit Feedback
- Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme
- A factorization criterion for acyclic directed mixed graphs
- Thomas Richardson
- Characterizing predictable classes of processes
- Daniil Ryabko
- Quantum Annealing for Variational Bayes Inference
- Issei Sato, Kenichi Kurihara, Shu Tanaka, Hiroshi Nakagawa , Seiji Miyashita
- Modeling Discrete Interventional Data using Directed Cyclic Graphical Models
- Mark Schmidt, Kevin Murphy
- Bisimulation-based Approximate Lifted Inference
- Prithviraj Sen, Amol Deshpande, Lise Getoor
- A direct method for estimating a causal ordering in a linear non-Gaussian acyclic model
- Shohei Shimizu, Aapo Hyvärinen, Yoshinobu Kawahara, Takashi Washio
- Effects of Treatment on the Treated: Identification and Generalization
- Ilya Shpitser, Judea Pearl
- Products of Hidden Markov Models: It Takes N>1 to Tango
- Graham Taylor, Geoffrey Hinton
- Measuring Inconsistency in Probabilistic Knowledge Bases
- Matthias Thimm
- Computing Posterior Probabilities of Structural Features in Bayesian Networks
- Jin Tian, Ru He
- Ordinal Boltzmann Machines for Collaborative Filtering
- Tran The Truyen, Dinh Phung, Svetha Venkatesh
- Probabilistic Structured Predictors
- Shankar Vembu, Thomas Gärtner, Mario Boley
- Which Spatial Partition Trees are Adaptive to Intrinsic Dimension?
- Nakul Verma, Samory Kpotufe, Sanjoy Dasgupta
- Simulation-Based Game Theoretic Analysis of Keyword Auctions with Low-Dimensional Bidding Strategies
- Yevgeniy Vorobeychik
- Exploring compact reinforcement-learning representations with linear regression
- Thomas Walsh, Istvan Szita, Carlos Diuk, Michael Littman
- Herding Dynamic Weights for Partially Observed Random Field Models
- Max Welling
- The Infinite Latent Events Model
- David Wingate, Noah Goodman, Daniel Roy, Josh Tenenbaum
- A Bayesian Framework for Community Detection Integrating Content and Link
- Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu
- The Entire Quantile Path of a Risk-Agnostic SVM Classifier
- Jin Yu, S V N Vishwanathan, Jian Zhang
- Most Relevant Explanation: Properties, Algorithms, and Evaluations
- Changhe Yuan, Xiaolu Liu, Tsai-Ching Lu, Heejin Lim
- A Uniqueness Theorem for Clustering
- Reza Bosagh Zadeh, Shai Ben-David
- On the Identifiability of the Post-Nonlinear Causal Model
- Kun Zhang, Aapo Hyvärinen
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