← Learning Types
Machine Learning › Learning Types ›

Online Learning

1012 directly classified papers

Papers per year

Papers

Mind the Duality Gap: Logarithmic regret algorithms for online optimization NIPS 2008
An Online Algorithm for Maximizing Submodular Functions NIPS 2008
Algorithms for Infinitely Many-Armed Bandits NIPS 2008
From Online to Batch Learning with Cutoff-Averaging NIPS 2008
Progressive mixture rules are deviation suboptimal NIPS 2007
Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts JMLR 2007
The Price of Bandit Information for Online Optimization NIPS 2007
On higher-order perceptron algorithms NIPS 2007
FilterBoost: Regression and Classification on Large Datasets NIPS 2007
Adaptive Online Gradient Descent NIPS 2007
The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information NIPS 2007
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning NIPS 2007
Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria NIPS 2007
Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs NIPS 2007
Online Linear Regression and Its Application to Model-Based Reinforcement Learning NIPS 2007
Incremental Support Vector Learning: Analysis, Implementation and Applications JMLR 2006
Worst-Case Analysis of Selective Sampling for Linear Classification JMLR 2006
Online Passive-Aggressive Algorithms JMLR 2006
Prediction on a Graph with a Perceptron NIPS 2006
Online Classification for Complex Problems Using Simultaneous Projections NIPS 2006
Convex Repeated Games and Fenchel Duality NIPS 2006
Handling Advertisements of Unknown Quality in Search Advertising NIPS 2006
Online Clustering of Moving Hyperplanes NIPS 2006
Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning NIPS 2006
Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension NIPS 2006