Uncertainty in Artificial Intelligence
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Proceedings of the Twenty-Ninth Conference Conference on Uncertainty in Artificial Intelligence ( 2013 )
Aug 11-15 2013, Bellevue, WA

Edited By:
Ann Nicholson, Padhraic Smyth
Published By: AUAI Press, Corvallis, Oregon
ISBN: -

A Sound and Complete Algorithm for Learning Causal Models from Relational Data
Marc Maier , Katerina Marazopoulou , David Arbour , David Jensen
Active Learning with Expert Advice
Peilin Zhao , Steven Hoi , Jinfeng Zhuang
Active Sensing as Bayes-Optimal Sequential Decision Making
Sheeraz Ahmad , Angela Yu
Advances in Bayesian Network Learning using Integer Programming
James Cussens , Mark Bartlett
Approximate Kalman Filter Q-Learning for Continuous State-Space MDPs
Charles Tripp , Ross Shachter
Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes
Patrice Perny , Paul Weng , Judy Goldsmith , Josiah Hanna
Automorphism Groups of Graphical Models and Lifted Variational Inference
Hung Bui , Tuyen Huynh , Sebastian Riedel
Batch-iFDD for Representation Expansion in Large MDPs
Alborz Geramifard , Thomas Walsh , Nicholas Roy , Jonathan How
Bennett-type Generalization Bounds: Large-deviation Case and Faster Rate of Convergence
Chao Zhang
Bethe-ADMM for Tree Decomposition based Parallel MAP Inference
Qiang Fu , Huahua Wang , Arindam Banerjee
Beyond Log-Supermodularity: Lower Bounds and the Bethe Partition Function
Nicholas Ruozzi
Boosting in the presence of label noise
Jakramate Bootkrajang , Ata Kaban
Bounded Approximate Symbolic Dynamic Programming for Hybrid MDPs
Luis Vianna , Scott Sanner , Leliane Nunes de Barros
Building Bridges: Viewing Active Learning from the Multi-Armed Bandit Lens
Ravi Ganti , Alexander Gray
Calculation of Entailed Rank Constraints in Partially Non-Linear and Cyclic Models
Peter Spirtes
Causal Transportability of Experiments on Controllable Subsets of Variables: z-Transportability
Sanghack Lee , Vasant Honavar
Collective Diffusion Over Networks: Models and Inference
Akshat Kumar , Daniel Sheldon , Biplav Srivastava
Constrained Bayesian Inference for Low Rank Multitask Learning
Oluwasanmi Koyejo , Joydeep Ghosh
Convex Relaxations of Bregman Divergence Clustering
Hao Cheng , Xinhua Zhang , Dale Schuurmans
Cyclic Causal Discovery from Continuous Equilibrium Data
Joris Mooij , Tom Heskes
Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering
Amar Shah , Zoubin Ghahramani
Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure
Antti Hyttinen , Patrik Hoyer , Frederick Eberhardt , Matti Jarvisalo
Dynamic Blocking and Collapsing for Gibbs Sampling
Deepak Venugopal , Vibhav Gogate
Evaluating Anytime Algorithms for Learning Optimal Bayesian Networks
Brandon Malone , Changhe Yuan
Evaluating computational models of explanation using human judgments
Michael Pacer , Joseph Williams , Xi Chen , Tania Lombrozo , Thomas Griffiths
Finite-Time Analysis of Kernelised Contextual Bandits
Michal Valko , Nathaniel Korda , Remi Munos , Ilias Flaounas , Nelo Cristianini
From Ordinary Differential Equations to Structural Causal Models: the deterministic case
Joris Mooij , Dominik Janzing , Bernhard Schoelkopf
Gaussian Processes for Big Data
James Hensman , Nicolo Fusi , Neil Lawrence
Generative Multiple-Instance Learning Models For Quantitative Electromyography
Tameem Adel , Benn Smith , Ruth Urner , Daniel Stashuk , Daniel Lizotte
High-dimensional Joint Sparsity Random Effects Model for Multi-task Learning
Krishnakumar Balasubramanian , Kai Yu , Tong Zhang
Hilbert Space Embeddings of Predictive State Representations
Byron Boots , Geoffrey Gordon , Arthur Gretton
Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction
Stephen Bach , Bert Huang , Ben London , Lise Getoor
Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders
Eleni Sgouritsa , Dominik Janzing , Jonas Peters , Bernhard Schoelkopf
Integrating Document Clustering and Topic Modeling
Pengtao Xie , Eric Xing
Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse Models
Jean Honorio , Tommi Jaakkola
Learning Max-Margin Tree Predictors
Ofer Meshi , Elad Eban , Gal Elidan , Amir Globerson
Learning Periodic Human Behaviour Models from Sparse Data for Crowdsourcing Aid Delivery in Developing Countries
James McInerney , Alex Rogers , Nicholas Jennings
Learning Sparse Causal Models is not NP-hard
Tom Claassen , Joris Mooij , Tom Heskes
Lower Bounds for Exact Model Counting and Applications in Probabilistic Databases
Paul Beame , Jerry Li , Sudeepa Roy , Dan Suciu
Modeling Documents with Deep Boltzmann Machines
Nitish Srivastava , Ruslan Salakhutdinov , Geoffrey Hinton
Monte-Carlo Planning: Theoretically Fast Convergence Meets Practical Efficiency
Zohar Feldman , Carmel Domshlak
Multiple Instance Learning by Discriminative Training of Markov Networks
Hossein Hajimirsadeghi , Jinling Li , Greg Mori , Mohammad Zaki , Tarek Sayed
Normalized Online Learning
Stephane Ross , Paul Mineiro , John Langford
On MAP Inference by MWSS on Perfect Graphs
Adrian Weller , Tony Jebara
On the Complexity of Strong and Epistemic Credal Networks
Denis Maua , Cassio de Campos , Alessio Benavoli , Alessandro Antonucci
One-Class Support Measure Machines for Group Anomaly Detection
Krikamol Muandet , Bernhard Schoelkopf
Optimization With Parity Constraints: From Binary Codes to Discrete Integration
Stefano Ermon , Carla Gomes , Ashish Sabharwal , Bart Selman
Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations
Jie Chen , Nannan Cao , Kian Hsiang Low , Ruofei Ouyang , Colin Keng-Yan Tan , Patrick Jaillet
Pay or Play
Sigal Oren , Michael Schapira , Moshe Tennenholtz
POMDPs under Probabilistic Semantics
Krishnendu Chatterjee , Martin Chmelik
Preference Elicitation For General Random Utility Models
Hossein Soufiani , David Parkes , Lirong Xia
Probabilistic Conditional Preference Networks
Damien Bigot , Bruno Zanuttini , Helene Fargier , Jerome Mengin
Probabilistic inverse reinforcement learning in unknown environments
Aristide Tossou , Christos Dimitrakakis
Qualitative Possibilistic Mixed-Observable MDPs
Nicolas Drougard , Florent Teichteil-Konigsbuch , Jean-Loup Farges , Didier Dubois
Reasoning about Probabilities in Dynamic Systems using Goal Regression
Vaishak Belle , Hector Levesque
Sample Complexity of Multi-task Reinforcement Learning
Emma Brunskill , Lihong Li
Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality
Vikas Sindhwani , Ha Quang Minh , Aurelie Lozano
Scoring and Searching over Bayesian Networks with Causal and Associative Priors
Giorgos Borboudakis , Ioannis Tsamardinos
Solution Methods for Constrained Markov Decision Process with Continuous Probability Modulation
Marek Petrik , Dharmashankar Subramanian , Janusz Marecki
Solving Limited-Memory Influence Diagrams Using Branch-and-Bound Search
Arindam Khaled , Eric Hansen , Changhe Yuan
Sparse Nested Markov models with Log-linear Parameters
Ilya Shpitser , Robin Evans , Thomas Richardson , James Robins
SparsityBoost: A New Scoring Function for Learning Bayesian Network Structure
Eliot Brenner , David Sontag
Speedy Model Selection (SMS) for Copula Models
Yaniv Tenzer , Gal Elidan
Stochastic Rank Aggregation
Shuzi Niu , Yanyan Lan , Jiafeng Guo , Xueqi Cheng
Structured Convex Optimization under Submodular Constraints
Kiyohito Nagano , Yoshinobu Kawahara
Structured Message Passing
Vibhav Gogate , Pedro Domingos
The Bregman Variational Dual-Tree Framework
Saeed Amizadeh , Bo Thiesson , Milos Hauskrecht
The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web ranking
Rishabh Iyer , Jeff Bilmes
The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models
Novi Quadrianto , Viktoriia Sharmanska , David Knowles , Zoubin Ghahramani
Tighter Linear Program Relaxations for High Order Graphical Models
Elad Mezuman , Daniel Tarlow , Amir Globerson , Yair Weiss
Treedy: A Heuristic for Counting and Sampling Subsets
Teppo Niinimaki , Mikko Koivisto
Unsupervised Learning of Noisy-Or Bayesian Networks
Yonatan Halpern , David Sontag
Warped Mixtures for Nonparametric Cluster Shapes
Tomoharu Iwata , David Duvenaud , Zoubin Ghahramani

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