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Online Learning

1012 directly classified papers

Papers per year

Papers

Iterative Learning for Reliable Crowdsourcing Systems NIPS 2011
Committing Bandits NIPS 2011
From Bandits to Experts: On the Value of Side-Observations NIPS 2011
Prediction strategies without loss NIPS 2011
Learning Eigenvectors for Free NIPS 2011
Bounds on Individual Risk for Log-loss Predictors COLT 2011
Efficient Online Learning via Randomized Rounding NIPS 2011
Adaptive Hedge NIPS 2011
Stochastic convex optimization with bandit feedback NIPS 2011
Robust approachability and regret minimization in games with partial monitoring COLT 2011
Nonlinear Online Classification Algorithm with Probability Margin ACML 2011
Online Learning: Stochastic, Constrained, and Smoothed Adversaries NIPS 2011
Multi-armed bandits on implicit metric spaces NIPS 2011
Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization COLT 2011
Online Learning of Multiple Tasks and Their Relationships AISTATS 2011
Online Learning of Structured Predictors with Multiple Kernels AISTATS 2011
Predicting Dynamic Difficulty NIPS 2011
Online Learning: Beyond Regret COLT 2011
A simple multi-armed bandit algorithm with optimal variation-bounded regret COLT 2011
Does an Efficient Calibrated Forecasting Strategy Exist? COLT 2011
On the Universality of Online Mirror Descent NIPS 2011
Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction NIPS 2011
Regret Bounds for the Adaptive Control of Linear Quadratic Systems COLT 2011
Blackwell Approachability and No-Regret Learning are Equivalent COLT 2011
Bandits, Query Learning, and the Haystack Dimension COLT 2011