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Publication search results
found 74 matches
- 2013
- Tameem Adel, Benn Smith, Ruth Urner, Daniel W. Stashuk, Daniel J. Lizotte:
Generative Multiple-Instance Learning Models For Quantitative Electromyography. UAI 2013 - Sheeraz Ahmad, Angela J. Yu:
Active Sensing as Bayes-Optimal Sequential Decision Making. UAI 2013 - Saeed Amizadeh, Bo Thiesson, Milos Hauskrecht:
The Bregman Variational Dual-Tree Framework. UAI 2013 - Stephen H. Bach, Bert Huang, Ben London, Lise Getoor:
Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction. UAI 2013 - Krishnakumar Balasubramanian, Kai Yu, Tong Zhang:
High-dimensional Joint Sparsity Random Effects Model for Multi-task Learning. UAI 2013 - Paul Beame, Jerry Li, Sudeepa Roy, Dan Suciu:
Lower Bounds for Exact Model Counting and Applications in Probabilistic Databases. UAI 2013 - Vaishak Belle, Hector J. Levesque:
Reasoning about Probabilities in Dynamic Systems using Goal Regression. UAI 2013 - Damien Bigot, Bruno Zanuttini, Hélène Fargier, Jérôme Mengin:
Probabilistic Conditional Preference Networks. UAI 2013 - Jakramate Bootkrajang, Ata Kabán:
Boosting in the presence of label noise. UAI 2013 - Byron Boots, Geoffrey J. Gordon, Arthur Gretton:
Hilbert Space Embeddings of Predictive State Representations. UAI 2013 - Giorgos Borboudakis, Ioannis Tsamardinos:
Scoring and Searching over Bayesian Networks with Causal and Associative Priors. UAI 2013 - Eliot Brenner, David A. Sontag:
SparsityBoost: A New Scoring Function for Learning Bayesian Network Structure. UAI 2013 - Emma Brunskill, Lihong Li:
Sample Complexity of Multi-task Reinforcement Learning. UAI 2013 - Hung Bui, Tuyen N. Huynh, Sebastian Riedel:
Automorphism Groups of Graphical Models and Lifted Variational Inference. UAI 2013 - Krishnendu Chatterjee, Martin Chmelik:
POMDPs under Probabilistic Semantics. UAI 2013 - Jie Chen, Nannan Cao, Kian Hsiang Low, Ruofei Ouyang, Colin Keng-Yan Tan, Patrick Jaillet:
Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations. UAI 2013 - Hao Cheng, Xinhua Zhang, Dale Schuurmans:
Convex Relaxations of Bregman Divergence Clustering. UAI 2013 - Tom Claassen, Joris M. Mooij, Tom Heskes:
Learning Sparse Causal Models is not NP-hard. UAI 2013 - James Cussens, Mark Bartlett:
Advances in Bayesian Network Learning using Integer Programming. UAI 2013 - Nicolas Drougard, Florent Teichteil-Königsbuch, Jean-Loup Farges, Didier Dubois:
Qualitative Possibilistic Mixed-Observable MDPs. UAI 2013 - Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman:
Optimization With Parity Constraints: From Binary Codes to Discrete Integration. UAI 2013 - Zohar Feldman, Carmel Domshlak:
Monte-Carlo Planning: Theoretically Fast Convergence Meets Practical Efficiency. UAI 2013 - Qiang Fu, Huahua Wang, Arindam Banerjee:
Bethe-ADMM for Tree Decomposition based Parallel MAP Inference. UAI 2013 - Ravi Ganti, Alexander G. Gray:
Building Bridges: Viewing Active Learning from the Multi-Armed Bandit Lens. UAI 2013 - Alborz Geramifard, Thomas J. Walsh, Nicholas Roy, Jonathan P. How:
Batch-iFDD for Representation Expansion in Large MDPs. UAI 2013 - Vibhav Gogate, Pedro M. Domingos:
Structured Message Passing. UAI 2013 - Hossein Hajimirsadeghi, Jinling Li, Greg Mori, Mohamed H. Zaki, Tarek Sayed:
Multiple Instance Learning by Discriminative Training of Markov Networks. UAI 2013 - Yonatan Halpern, David A. Sontag:
Unsupervised Learning of Noisy-Or Bayesian Networks. UAI 2013 - James Hensman, Nicoló Fusi, Neil D. Lawrence:
Gaussian Processes for Big Data. UAI 2013 - Jean Honorio, Tommi S. Jaakkola:
Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse Models. UAI 2013
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