← Optimization & Theory
Machine Learning › Optimization & Theory ›

Learning Theory

5312 directly classified papers

Papers per year

Papers

Information-Theoretic Characterization of Sparse Recovery AISTATS 2014
On the convergence of no-regret learning in selfish routing ICML 2014
Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing ICML 2014
Nonparametric Estimation of Multi-View Latent Variable Models ICML 2014
Reducing Dueling Bandits to Cardinal Bandits ICML 2014
Hard-Margin Active Linear Regression ICML 2014
Maximum Margin Multiclass Nearest Neighbors ICML 2014
Deep Boosting ICML 2014
Efficient learning by implicit exploration in bandit problems with side observations NIPS 2014
Improved Bounds for Online Learning Over the Permutahedron and Other Ranking Polytopes AISTATS 2014
PAC-Bayesian Collective Stability AISTATS 2014
Online Non-Parametric Regression COLT 2014
A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates COLT 2014
The Complexity of Learning Halfspaces using Generalized Linear Methods COLT 2014
Provable Bounds for Learning Some Deep Representations ICML 2014
Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint ICML 2014
Condensed Filter Tree for Cost-Sensitive Multi-Label Classification ICML 2014
Generalized Exponential Concentration Inequality for Renyi Divergence Estimation ICML 2014
Learning Theory and Algorithms for revenue optimization in second price auctions with reserve ICML 2014
A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data ICML 2014
Hardness of parameter estimation in graphical models NIPS 2014
On the Statistical Consistency of Plug-in Classifiers for Non-decomposable Performance Measures NIPS 2014
QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models NIPS 2014
Near-optimal sample compression for nearest neighbors NIPS 2014
Optimal Teaching for Limited-Capacity Human Learners NIPS 2014