Papers
176,624 papers found
Matched Gene Selection and Committee Classifier for Molecular Classification of Heterogeneous Diseases
Guoqiang Yu, Yuanjian Feng, David J. Miller et al.
Matrix-Variate Dirichlet Process Mixture Models
Zhihua Zhang, Guang Dai, Michael I. Jordan
Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds
Jacek P. Dmochowski, Paul Sajda, Lucas C. Parra
Maximum-likelihood learning of cumulative distribution functions on graphs
Jim Huang, Nebojsa Jojic
Maximum Relative Margin and Data-Dependent Regularization
Pannagadatta K. Shivaswamy, Tony Jebara
Mean Field Variational Approximation for Continuous-Time Bayesian Networks
Ido Cohn, Tal El-Hay, Nir Friedman et al.
Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes
Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwright
Minimum Average Cost Clustering
Kiyohito Nagano, Yoshinobu Kawahara, Satoru Iwata
Mining Recurring Concept Drifts with Limited Labeled Streaming Data
Peipei Li, Xindong Wu, Xuegang Hu
Mixture of time-warped trajectory models for movement decoding
Elaine Corbett, Eric Perreault, Konrad Koerding
MOA: Massive Online Analysis
Albert Bifet, Geoff Holmes, Richard Kirkby et al.
Model-based Boosting 2.0
Torsten Hothorn, Peter Bühlmann, Thomas Kneib et al.
Model-Free Monte Carlo-like Policy Evaluation
Raphael Fonteneau, Susan Murphy, Louis Wehenkel et al.
Modeling annotator expertise: Learning when everybody knows a bit of something
Yan Yan, Romer Rosales, Glenn Fung et al.
Model Selection: Beyond the Bayesian/Frequentist Divide
Isabelle Guyon, Amir Saffari, Gideon Dror et al.
Monte-Carlo Planning in Large POMDPs
David Silver, Joel Veness
Moreau-Yosida Regularization for Grouped Tree Structure Learning
Jun Liu, Jieping Ye
More data means less inference: A pseudo-max approach to structured learning
David Sontag, Ofer Meshi, Amir Globerson et al.
Motion planning under bounded uncertainty using ensemble control
A. Becker and T. Bretl
Movement extraction by detecting dynamics switches and repetitions
Silvia Chiappa, Jan R. Peters
Multiclass-Multilabel Classification with More Classes than Examples
Ofer Dekel, Ohad Shamir
Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition
Serhat Bucak, Rong Jin, Anil K. Jain
Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers
Manas Pathak, Shantanu Rane, Bhiksha Raj
Multiple Kernel Learning and the SMO Algorithm
Zhaonan Sun, Nawanol Ampornpunt, Manik Varma et al.