Machine Learning with Operational Costs

Manifold Learning: The Price of Normalization

Manifold-Based Signal Recovery and Parameter Estimation from Compressive Measurements

Many-to-Many Graph Matching: a Continuous Relaxation Approach

Mask Iterative Hard Thresholding Algorithms for Sparse Image Reconstruction of Objects with Known Contour

Maximum Entropy Discrimination Markov Networks

Maximum Joint Entropy and Information-Based Collaboration of Automated Learning Machines

Maximum Likelihood Joint Tracking and Association in a Strong Clutter without Combinatorial Complexity

Mean-Field Theory of Meta-Learning

MedLDA: A General Framework of Maximum Margin Supervised Topic Models

Metric Embedding for Nearest Neighbor Classification

Minimax Manifold Estimation

Minimax Policies for Combinatorial Prediction Games

Minimax Rates for Homology Inference

Minimax Rates of Estimation for Sparse PCA in High Dimensions

Missing Data using Decision Forest and Computational Intelligence

Mixed Cumulative Distribution Networks

Mixed-Membership Stochastic Block-Models for Transactional Networks

Mixtures of conditional Gaussian scale mixtures applied to multiscale image representations

Modern hierarchical, agglomerative clustering algorithms