Abstract is missing.
- Learning Sparse Causal Models is not NP-hardTom Claassen, Joris M. Mooij, Tom Heskes. [doi]
- The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web rankingRishabh K. Iyer, Jeff A. Bilmes. [doi]
- Warped Mixtures for Nonparametric Cluster ShapesTomoharu Iwata, David K. Duvenaud, Zoubin Ghahramani. [doi]
- Integrating Document Clustering and Topic ModelingPengtao Xie, Eric P. Xing. [doi]
- Active Sensing as Bayes-Optimal Sequential Decision MakingSheeraz Ahmad, Angela J. Yu. [doi]
- Bounded Approximate Symbolic Dynamic Programming for Hybrid MDPsLuis Gustavo Vianna, Scott Sanner, Leliane Nunes de Barros. [doi]
- Stochastic Rank AggregationShuzi Niu, Yanyan Lan, Jiafeng Guo, Xueqi Cheng. [doi]
- Solution Methods for Constrained Markov Decision Process with Continuous Probability ModulationMarek Petrik, Dharmashankar Subramanian, Janusz Marecki. [doi]
- Multiple Instance Learning by Discriminative Training of Markov NetworksHossein Hajimirsadeghi, Jinling Li, Greg Mori, Mohammad Zaki, Tarek Sayed. [doi]
- Preference Elicitation For General Random Utility ModelsHossein Azari Soufiani, David C. Parkes, Lirong Xia. [doi]
- Treedy: A Heuristic for Counting and Sampling SubsetsTeppo Niinimaki, Mikko Koivisto. [doi]
- Lower Bounds for Exact Model Counting and Applications in Probabilistic DatabasesPaul Beame, Jerry Li, Sudeepa Roy, Dan Suciu. [doi]
- Learning Periodic Human Behaviour Models from Sparse Data for Crowdsourcing Aid Delivery in Developing CountriesJames McInerney, Alex Rogers, Nicholas R. Jennings. [doi]
- Structured Message PassingVibhav Gogate, Pedro Domingos. [doi]
- Learning Max-Margin Tree PredictorsOfer Meshi, Elad Eban, Gal Elidan, Amir Globerson. [doi]
- Constrained Bayesian Inference for Low Rank Multitask LearningOluwasanmi Koyejo, Joydeep Ghosh. [doi]
- Reasoning about Probabilities in Dynamic Systems using Goal RegressionVaishak Belle, Hector J. Levesque. [doi]
- A Sound and Complete Algorithm for Learning Causal Models from Relational DataMarc E. Maier, Katerina Marazopoulou, David T. Arbour, David D. Jensen. [doi]
- Scoring and Searching over Bayesian Networks with Causal and Associative PriorsGiorgos Borboudakis, Ioannis Tsamardinos. [doi]
- Finite-Time Analysis of Kernelised Contextual BanditsMichal Valko, Nathaniel Korda, Rémi Munos, Ilias Flaounas, Nello Cristianini. [doi]
- Batch-iFDD for Representation Expansion in Large MDPsAlborz Geramifard, Thomas J. Walsh, Nicholas Roy, Jonathan P. How. [doi]
- Automorphism Groups of Graphical Models and Lifted Variational InferenceHung Hai Bui, Tuyen N. Huynh, Sebastian Riedel. [doi]
- High-dimensional Joint Sparsity Random Effects Model for Multi-task LearningKrishnakumar Balasubramanian, Kai Yu, Tong Zhang 0001. [doi]
- From Ordinary Differential Equations to Structural Causal Models: the deterministic caseJoris M. Mooij, Dominik Janzing, Bernhard Schölkopf. [doi]
- Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse ModelsJean Honorio, Tommi Jaakkola. [doi]
- Generative Multiple-Instance Learning Models For Quantitative ElectromyographyTameem Adel, Benn Smith, Ruth Urner, Daniel W. Stashuk, Daniel J. Lizotte. [doi]
- Calculation of Entailed Rank Constraints in Partially Non-Linear and Cyclic ModelsPeter Spirtes. [doi]
- Beyond Log-Supermodularity: Lower Bounds and the Bethe Partition FunctionNicholas Ruozzi. [doi]
- POMDPs under Probabilistic SemanticsKrishnendu Chatterjee, Martin Chmelik. [doi]
- Monte-Carlo Planning: Theoretically Fast Convergence Meets Practical EfficiencyZohar Feldman, Carmel Domshlak. [doi]
- Gaussian Processes for Big DataJames Hensman, Nicoló Fusi, Neil D. Lawrence. [doi]
- Modeling Documents with Deep Boltzmann MachinesNitish Srivastava, Ruslan Salakhutdinov, Geoffrey E. Hinton. [doi]
- Evaluating Anytime Algorithms for Learning Optimal Bayesian NetworksBrandon M. Malone, Changhe Yuan. [doi]
- Hilbert Space Embeddings of Predictive State RepresentationsByron Boots, Geoffrey J. Gordon, Arthur Gretton. [doi]
- SparsityBoost: A New Scoring Function for Learning Bayesian Network StructureEliot Brenner, David Sontag. [doi]
- The Bregman Variational Dual-Tree FrameworkSaeed Amizadeh, Bo Thiesson, Milos Hauskrecht. [doi]
- Cyclic Causal Discovery from Continuous Equilibrium DataJoris M. Mooij, Tom Heskes. [doi]
- Causal Transportability of Experiments on Controllable Subsets of Variables: z-TransportabilitySanghack Lee, Vasant Honavar. [doi]
- Dynamic Blocking and Collapsing for Gibbs SamplingDeepak Venugopal, Vibhav Gogate. [doi]
- Hinge-loss Markov Random Fields: Convex Inference for Structured PredictionStephen H. Bach, Bert Huang, Ben London, Lise Getoor. [doi]
- Building Bridges: Viewing Active Learning from the Multi-Armed Bandit LensRavi Ganti, Alexander G. Gray. [doi]
- Probabilistic Conditional Preference NetworksDamien Bigot, Bruno Zanuttini, Hélène Fargier, Jérôme Mengin. [doi]
- Normalized Online LearningStéphane Ross, Paul Mineiro, John Langford. [doi]
- Collective Diffusion Over Networks: Models and InferenceAkshat Kumar, Daniel Sheldon, Biplav Srivastava. [doi]
- Bethe-ADMM for Tree Decomposition based Parallel MAP InferenceQiang Fu, Huahua Wang, Arindam Banerjee. [doi]
- Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based ProcedureAntti Hyttinen, Patrik O. Hoyer, Frederick Eberhardt, Matti Järvisalo. [doi]
- Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised ClusteringAmar Shah, Zoubin Ghahramani. [doi]
- Pay or PlaySigal Oren, Michael Schapira, Moshe Tennenholtz. [doi]
- The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature ModelsNovi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani. [doi]
- Boosting in the presence of label noiseJakramate Bootkrajang, Ata Kabán. [doi]
- Approximate Kalman Filter Q-Learning for Continuous State-Space MDPsCharles Tripp, Ross D. Shachter. [doi]
- Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of ConfoundersEleni Sgouritsa, Dominik Janzing, Jonas Peters, Bernhard Schölkopf. [doi]
- Optimization With Parity Constraints: From Binary Codes to Discrete IntegrationStefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman. [doi]
- Evaluating computational models of explanation using human judgmentsMichael Pacer, Joseph Jay Williams, Xi Chen, Tania Lombrozo, Thomas L. Griffiths. [doi]
- On the Complexity of Strong and Epistemic Credal NetworksDenis Deratani Mauá, Cassio Polpo de Campos, Alessio Benavoli, Alessandro Antonucci. [doi]
- Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision ProcessesPatrice Perny, Paul Weng, Judy Goldsmith, Josiah Hanna. [doi]
- Tighter Linear Program Relaxations for High Order Graphical ModelsElad Mezuman, Daniel Tarlow, Amir Globerson, Yair Weiss. [doi]
- Active Learning with Expert AdvicePeilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang. [doi]
- Parallel Gaussian Process Regression with Low-Rank Covariance Matrix ApproximationsJie Chen, Nannan Cao, Kian Hsiang Low, Ruofei Ouyang, Colin Keng-Yan Tan, Patrick Jaillet. [doi]
- Structured Convex Optimization under Submodular ConstraintsKiyohito Nagano, Yoshinobu Kawahara. [doi]
- Bennett-type Generalization Bounds: Large-deviation Case and Faster Rate of ConvergenceChao Zhang. [doi]
- One-Class Support Measure Machines for Group Anomaly DetectionKrikamol Muandet, Bernhard Schölkopf. [doi]
- Unsupervised Learning of Noisy-Or Bayesian NetworksYonatan Halpern, David Sontag. [doi]
- Qualitative Possibilistic Mixed-Observable MDPsNicolas Drougard, Florent Teichteil-Königsbuch, Jean-Loup Farges, Didier Dubois. [doi]
- Sample Complexity of Multi-task Reinforcement LearningEmma Brunskill, Lihong Li. [doi]
- Convex Relaxations of Bregman Divergence ClusteringHao Cheng, Xinhua Zhang, Dale Schuurmans. [doi]
- Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger CausalityVikas Sindhwani, Ha Quang Minh, Aurelie C. Lozano. [doi]
- Sparse Nested Markov models with Log-linear ParametersIlya Shpitser, Robin J. Evans, Thomas S. Richardson, James M. Robins. [doi]
- Solving Limited-Memory Influence Diagrams Using Branch-and-Bound SearchArindam Khaled, Eric A. Hansen, Changhe Yuan. [doi]
- Probabilistic inverse reinforcement learning in unknown environmentsAristide C. Y. Tossou, Christos Dimitrakakis. [doi]
- On MAP Inference by MWSS on Perfect GraphsAdrian Weller, Tony Jebara. [doi]
- Advances in Bayesian Network Learning using Integer ProgrammingJames Cussens, Mark Bartlett. [doi]
- Speedy Model Selection (SMS) for Copula ModelsYaniv Tenzer, Gal Elidan. [doi]