conftrace_
← Optimization & Theory
Machine Learning › Optimization & Theory ›

Learning Theory

5,334 papers

Papers per year

17
66
123
466
307
'05
'10
'15
'20
'25

Papers

Recursive Teaching Dimension, VC-Dimension and Sample Compression JMLR 2014
Matrix Completion with the Trace Norm: Learning, Bounding, and Transducing JMLR 2014
On the Bayes-Optimality of F-Measure Maximizers JMLR 2014
New Results for Random Walk Learning JMLR 2014
Learning to locate from demonstrated searches RSS 2014
Probably Approximately Correct MDP Learning and Control With Temporal Logic Constraints RSS 2014
On model selection consistency of penalized M-estimators: a geometric theory NIPS 2013
Reinforcement Learning in Robust Markov Decision Processes NIPS 2013
A Gang of Bandits NIPS 2013
Matrix factorization with binary components NIPS 2013
Tracking Time-varying Graphical Structure NIPS 2013
Estimation, Optimization, and Parallelism when Data is Sparse NIPS 2013
Predictive PAC Learning and Process Decompositions NIPS 2013
Adaptivity to Local Smoothness and Dimension in Kernel Regression NIPS 2013
Learning with Noisy Labels NIPS 2013
Prior-free and prior-dependent regret bounds for Thompson Sampling NIPS 2013
Eluder Dimension and the Sample Complexity of Optimistic Exploration NIPS 2013
Estimating the Unseen: Improved Estimators for Entropy and other Properties NIPS 2013
Online learning in episodic Markovian decision processes by relative entropy policy search NIPS 2013
Error-Minimizing Estimates and Universal Entry-Wise Error Bounds for Low-Rank Matrix Completion NIPS 2013
The Pareto Regret Frontier NIPS 2013
On the Representational Efficiency of Restricted Boltzmann Machines NIPS 2013
Statistical Active Learning Algorithms NIPS 2013
Analyzing the Harmonic Structure in Graph-Based Learning NIPS 2013
More data speeds up training time in learning halfspaces over sparse vectors NIPS 2013