UAI 2016
100 papers
A Probabilistic Approach for Detection and Analysis of Cognitive Flow
Debatri Chatterjee, Aniruddha Sinha, Meghamala Sinha, Sanjoy Kumar Saha Bayesian Hyperparameter Optimization for Ensemble Learning
Julien-Charles Levesque, Christian Gagné, Robert Sabourin Bayesian Learning of Kernel Embeddings
Seth R. Flaxman, Dino Sejdinovic, John P. Cunningham, Sarah Filippi Bounded Rationality in Wagering Mechanisms
David M. Pennock, Vasilis Syrgkanis, Jennifer Wortman Vaughan Budgeted Semi-Supervised Support Vector Machine
Trung Le, Phuong Duong, Mi Dinh, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung Cascading Bandits for Large-Scale Recommendation Problems
Shi Zong, Hao Ni, Kenny Sung, Nan Rosemary Ke, Zheng Wen, Branislav Kveton Context-Dependent Feature Analysis with Random Forests
Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts Correlated Tag Learning in Topic Model
Shuangyin Li, Rong Pan, Yu Zhang, Qiang Yang Efficient Feature Group Sequencing for Anytime Linear Prediction
Hanzhang Hu, Alexander Grubb, J. Andrew Bagnell, Martial Hebert Efficient Multi-Class Selective Sampling on Graphs
Peng Yang, Peilin Zhao, Zhen Hai, Wei Liu, Steven C. H. Hoi, Xiaoli Li Finite Sample Complexity of Rare Pattern Anomaly Detection
Md Amran Siddiqui, Alan Fern, Thomas G. Dietterich, Shubhomoy Das Gradient Methods for Stackelberg Games
Kareem Amin, Michael P. Wellman, Satinder Singh Hierarchical Learning of Grids of Microtopics
Nebojsa Jojic, Alessandro Perina, Dongwoo Kim Individual Planning in Open and Typed Agent Systems
Muthukumaran Chandrasekaran, Adam Eck, Prashant Doshi, Leenkiat Soh Inferring Causal Direction from Relational Data
David T. Arbour, Katerina Marazopoulou, David D. Jensen Learning to Smooth with Bidirectional Predictive State Inference Machines
Wen Sun, Roberto Capobianco, Geoffrey J. Gordon, J. Andrew Bagnell, Byron Boots Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting
Pengtao Xie, Jin Kyu Kim, Yi Zhou, Qirong Ho, Abhimanu Kumar, Yaoliang Yu, Eric P. Xing Marginal Causal Consistency in Constraint-Based Causal Learning
Anna Roumpelaki, Giorgos Borboudakis, Sofia Triantafillou, Ioannis Tsamardinos MDPs with Unawareness in Robotics
Nan Rong, Joseph Y. Halpern, Ashutosh Saxena Model-Free Reinforcement Learning with Skew-Symmetric Bilinear Utilities
Hugo Gilbert, Bruno Zanuttini, Paul Weng, Paolo Viappiani, Esther Nicart Modeling Transitivity in Complex Networks
Morteza Haghir Chehreghani, Mostafa Haghir Chehreghani Online Bayesian Multiple Kernel Bipartite Ranking
Changying Du, Changde Du, Guoping Long, Qing He, Yucheng Li Overdispersed Black-Box Variational Inference
Francisco J. R. Ruiz, Michalis K. Titsias, David M. Blei Safely Interruptible Agents
Laurent Orseau, Stuart Armstrong Scalable Nonparametric Bayesian Multilevel Clustering
Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui Separating Sparse Signals from Correlated Noise in Binary Classification
Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert, Marius Kloft Stability of Causal Inference
Leonard J. Schulman, Piyush Srivastava Subspace Clustering with a Twist
David P. Wipf, Yue Dong, Bo Xin Super-Sampling with a Reservoir
Brooks Paige, Dino Sejdinovic, Frank D. Wood The Mondrian Kernel
Matej Balog, Balaji Lakshminarayanan, Zoubin Ghahramani, Daniel M. Roy, Yee Whye Teh