Papers
Logistic Stick-Breaking Process
Lu Ren, Lan Du, Lawrence Carin et al.
Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas
Vitaly Feldman, Homin K. Lee, Rocco A. Servedio
Lower Bounds for Passive and Active Learning
Maxim Raginsky, Alexander Rakhlin
LPmade: Link Prediction Made Easy
Ryan N. Lichtenwalter, Nitesh V. Chawla
Lying Pose Recognition for Elderly Fall Detection
Simin Wang, Salim Zabir, Bastian Leibe
Machine Learning Markets
Amos Storkey
Manifold Precis: An Annealing Technique for Diverse Sampling of Manifolds
Nitesh Shroff, Pavan Turaga, Rama Chellappa
MAP Inference for Bayesian Inverse Reinforcement Learning
Jaedeug Choi, Kee-eung Kim
Matrix Completion for Multi-label Image Classification
Ricardo S. Cabral, Fernando Torre, Joao P. Costeira et al.
Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning
Xinggang Wang, Xiang Bai, Xingwei Yang et al.
Maximum Covariance Unfolding : Manifold Learning for Bimodal Data
Vijay Mahadevan, Chi W. Wong, Jose C. Pereira et al.
Maximum Likelihood vs. Sequential Normalized Maximum Likelihood in On-line Density Estimation
Wojciech Kotłowski, Peter Grünwald
Maximum Margin Multi-Instance Learning
Hua Wang, Heng Huang, Farhad Kamangar et al.
Maximum Margin Multi-Label Structured Prediction
Christoph H. Lampert
Maximum Volume Clustering
Gang Niu, Bo Dai, Lin Shang et al.
Message-Passing for Approximate MAP Inference with Latent Variables
Jiarong Jiang, Piyush Rai, Hal Daume
Metric Learning with Multiple Kernels
Jun Wang, Huyen T. Do, Adam Woznica et al.
Microbagging Estimators: An Ensemble Approach to Distance-weighted Classifiers
Blaine Nelson, Battista Biggio, Pavel Laskov
Minimax Algorithm for Learning Rotations
Wojciech Kotłowski, Manfred K. Warmuth
Minimax Localization of Structural Information in Large Noisy Matrices
Mladen Kolar, Sivaraman Balakrishnan, Alessandro Rinaldo et al.
Minimax Policies for Combinatorial Prediction Games
Jean-Yves Audibert, Sébastien Bubeck, Gábor Lugosi
Minimax Regret of Finite Partial-Monitoring Games in Stochastic Environments
Gábor Bartók, Dávid Pál, Csaba Szepesvári
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
Paramveer S. Dhillon, Dean Foster, Lyle H. Ungar
Missing Information Impediments to Learnability
Loizos Michael