Stat-Ml
Linear Coupling: An Ultimate Unification of Gradient and Mirror Descent
DC approximation approaches for sparse optimization
Kernel Nonnegative Matrix Factorization Without the Curse of the Pre-image - Application to Unmixing Hyperspectral Images
Expanding the Family of Grassmannian Kernels: An Embedding Perspective
Entropic one-class classifiers
Cortical spatio-temporal dimensionality reduction for visual grouping
Inverse Graphics with Probabilistic CAD Models
Learning From Ordered Sets and Applications in Collaborative Ranking
Identifying Cover Songs Using Information-Theoretic Measures of Similarity
An eigenanalysis of data centering in machine learning
Density Adaptive Parallel Clustering
Practical Kernel-Based Reinforcement Learning
Bandits Warm-up Cold Recommender Systems
Dictionary Learning and Tensor Decomposition via the Sum-of-Squares Method
Private Learning and Sanitization: Pure vs. Approximate Differential Privacy
Collaborative Deep Learning for Recommender Systems
Zero Shot Recognition with Unreliable Attributes
A Method for Stopping Active Learning Based on Stabilizing Predictions and the Need for User-Adjustable Stopping
Distributed Clustering and Learning Over Networks
Beyond Maximum Likelihood: from Theory to Practice
The Role of Emotions in Propagating Brands in Social Networks
Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures
