Stat-Ml
A Machine Learning Perspective on Predictive Coding with PAQ
Towards automated symptoms assessment in mental health
On the Evaluation Criterions for the Active Learning Processes
Optimization with Sparsity-Inducing Penalties
Learning Neural Activations
Spatiotemporal Emotion Recognition using Deep CNN Based on EEG during Music Listening
Machine Learning for high speed channel optimization
Fast redshift clustering with the Baire (ultra) metric
Reliability-based design optimization using kriging surrogates and subset simulation
Efficient First Order Methods for Linear Composite Regularizers
Time Series Simulation by Conditional Generative Adversarial Net
Iterative Reweighted Algorithms for Sparse Signal Recovery with Temporally Correlated Source Vectors
Preference elicitation and inverse reinforcement learning
Clustering Partially Observed Graphs via Convex Optimization
Feedback Message Passing for Inference in Gaussian Graphical Models
Rank Minimization over Finite Fields: Fundamental Limits and Coding-Theoretic Interpretations
The Discrete Infinite Logistic Normal Distribution
Compressive Network Analysis
Online Learning: Stochastic and Constrained Adversaries
Fast global convergence of gradient methods for high-dimensional statistical recovery
Notes on a New Philosophy of Empirical Science
Generalized double Pareto shrinkage
