← Optimization & Theory
Machine Learning › Optimization & Theory ›

Online Algorithms

803 directly classified papers

Papers per year

Papers

Small-loss bounds for online learning with partial information COLT 2018
Normal Bandits of Unknown Means and Variances JMLR 2018
HONES: A Fast and Tuning-free Homotopy Method For Online Newton Step AISTATS 2018
Efficient tracking of a growing number of experts ALT 2017
Efficient Online Linear Optimization with Approximation Algorithms NIPS 2017
Online Learning and Blackwell Approachability with Partial Monitoring: Optimal Convergence Rates AISTATS 2017
Improved Strongly Adaptive Online Learning using Coin Betting AISTATS 2017
Retaining Data from Streams of Social Platforms with Minimal Regret IJCAI 2017
Random Permutation Online Isotonic Regression NIPS 2017
Parameter-Free Online Learning via Model Selection NIPS 2017
Learning Linear Dynamical Systems via Spectral Filtering NIPS 2017
Online Learning to Rank with Top-k Feedback JMLR 2017
Online multiclass boosting NIPS 2017
Identify the Nash Equilibrium in Static Games with Random Payoffs ICML 2017
Thresholding Bandits with Augmented UCB IJCAI 2017
Online Learning for Multivariate Hawkes Processes NIPS 2017
Efficient Second-Order Online Kernel Learning with Adaptive Embedding NIPS 2017
Online Learning to Rank in Stochastic Click Models ICML 2017
Identifying Outlier Arms in Multi-Armed Bandit NIPS 2017
Efficient Online Bandit Multiclass Learning with $\tilde{O}(\sqrt{T})$ Regret ICML 2017
Online Learning of Task-specific Word Representations with a Joint Biconvex Passive-Aggressive Algorithm EACL 2017
Efficient Benchmarking of NLP APIs using Multi-armed Bandits EACL 2017
Variants of RMSProp and Adagrad with Logarithmic Regret Bounds ICML 2017
Heuristic Online Goal Recognition in Continuous Domains IJCAI 2017
Dueling Bandits with Weak Regret ICML 2017