Papers
176,624 papers found
Manifold Embeddings for Model-Based Reinforcement Learning under Partial Observability
Keith Bush, Joelle Pineau
Manifold Regularization for SIR with Rate Root-n Convergence
Wei Bian, Dacheng Tao
Marginal Likelihood Integrals for Mixtures of Independence Models
Shaowei Lin, Bernd Sturmfels, Zhiqiang Xu
Margin-based Ranking and an Equivalence between AdaBoost and RankBoost
Cynthia Rudin, Robert E. Schapire
Markov Properties for Linear Causal Models with Correlated Errors
Changsung Kang, Jin Tian
Matrix Completion from Noisy Entries
Raghunandan Keshavan, Andrea Montanari, Sewoong Oh
Matrix Completion from Power-Law Distributed Samples
Raghu Meka, Prateek Jain, Inderjit S. Dhillon
Maximin affinity learning of image segmentation
Kevin Briggman, Winfried Denk, Sebastian Seung et al.
Maximum Entropy Discrimination Markov Networks
Jun Zhu, Eric P. Xing
Maximum likelihood trajectories for continuous-time Markov chains
Theodore J. Perkins
Measuring Invariances in Deep Networks
Ian Goodfellow, Honglak Lee, Quoc V. Le et al.
Measuring model complexity with the prior predictive
Wolf Vanpaemel
Modeling Social Annotation Data with Content Relevance using a Topic Model
Tomoharu Iwata, Takeshi Yamada, Naonori Ueda
Modeling the spacing effect in sequential category learning
Hongjing Lu, Matthew Weiden, Alan L. Yuille
Modelling Relational Data using Bayesian Clustered Tensor Factorization
Ilya Sutskever, Joshua B. Tenenbaum, Ruslan Salakhutdinov
Model Monitor (M2): Evaluating, Comparing, and Monitoring Models
Troy Raeder, Nitesh V. Chawla
Monte Carlo Sampling for Regret Minimization in Extensive Games
Marc Lanctot, Kevin Waugh, Martin Zinkevich et al.
Multi-Label Prediction via Compressed Sensing
Daniel J. Hsu, Sham M. Kakade, John Langford et al.
Multi-Label Prediction via Sparse Infinite CCA
Piyush Rai, Hal Daume
Multiple Incremental Decremental Learning of Support Vector Machines
Masayuki Karasuyama, Ichiro Takeuchi
Multi-Step Dyna Planning for Policy Evaluation and Control
Hengshuai Yao, Shalabh Bhatnagar, Dongcui Diao et al.
Multi-task Reinforcement Learning in Partially Observable Stochastic Environments
Hui Li, Xuejun Liao, Lawrence Carin
Nash Equilibria of Static Prediction Games
Michael Brückner, Tobias Scheffer
Nearest Neighbor Clustering: A Baseline Method for Consistent Clustering with Arbitrary Objective Functions
Sébastien Bubeck, Ulrike von Luxburg
Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling
Lei Shi, Thomas L. Griffiths