← Optimization & Theory
Machine Learning › Optimization & Theory ›

Statistical Learning

4076 directly classified papers

Papers per year

Papers

Robust Sparse Regression under Adversarial Corruption ICML 2013
Learning Spatio-Temporal Structure from RGB-D Videos for Human Activity Detection and Anticipation ICML 2013
On model selection consistency of penalized M-estimators: a geometric theory NIPS 2013
On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation NIPS 2013
Fantope Projection and Selection: A near-optimal convex relaxation of sparse PCA NIPS 2013
Cluster Trees on Manifolds NIPS 2013
Conditional Random Fields via Univariate Exponential Families NIPS 2013
Regression-tree Tuning in a Streaming Setting NIPS 2013
Estimating LASSO Risk and Noise Level NIPS 2013
Optimal kernel choice for large-scale two-sample tests NIPS 2012
On Estimation and Selection for Topic Models AISTATS 2012
Privacy Aware Learning NIPS 2012
Restricted Strong Convexity and Weighted Matrix Completion: Optimal Bounds with Noise JMLR 2012
Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders NIPS 2012
Bayesian estimation of discrete entropy with mixtures of stick-breaking priors NIPS 2012
Graphical Models via Generalized Linear Models NIPS 2012
A Spectral Algorithm for Latent Dirichlet Allocation NIPS 2012
The Perturbed Variation NIPS 2012
Kernel Hyperalignment NIPS 2012
Nonconvex Penalization Using Laplace Exponents and Concave Conjugates NIPS 2012
How They Vote: Issue-Adjusted Models of Legislative Behavior NIPS 2012
Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs NIPS 2012
Statistical Consistency of Ranking Methods in A Rank-Differentiable Probability Space NIPS 2012
Meta-Gaussian Information Bottleneck NIPS 2012
Ancestor Sampling for Particle Gibbs NIPS 2012