mistake bound

Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games COLT 2021 Toward a General Theory of Online Selective Sampling: Trading Off Mistakes and Queries AISTATS 2021 Exact Passive-Aggressive Algorithms for Multiclass Classification Using Bandit Feedbacks ACML 2020 Exploiting the Surrogate Gap in Online Multiclass Classification NeurIPS 2020 Online Active Learning of Reject Option Classifiers AAAI 2020 Online Prediction of Switching Graph Labelings with Cluster Specialists NeurIPS 2019 On Similarity Prediction and Pairwise Clustering ALT 2018 Efficient Online Multiclass Prediction on Graphs via Surrogate Losses AISTATS 2017 New bounds on the price of bandit feedback for mistake-bounded online multiclass learning ALT 2017 Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs NeurIPS 2016 Mistake Bounds for Binary Matrix Completion NeurIPS 2016 Quantum Perceptron Models NeurIPS 2016 The Extended Littlestone’s Dimension for Learning with Mistakes and Abstentions COLT 2016 Online Prediction at the Limit of Zero Temperature NeurIPS 2015 Predicting a Switching Sequence of Graph Labelings JMLR 2015 Predtron: A Family of Online Algorithms for General Prediction Problems NeurIPS 2015 Selective Sampling with Drift AISTATS 2014 Random Spanning Trees and the Prediction of Weighted Graphs JMLR 2013 A Linear Time Active Learning Algorithm for Link Classification NeurIPS 2012 Attribute-Efficient Learning andWeight-Degree Tradeoffs for Polynomial Threshold Functions COLT 2012 New Bounds for Learning Intervals with Implications for Semi-Supervised Learning COLT 2012 Active Learning with a Drifting Distribution NeurIPS 2011 Nonlinear Online Classification Algorithm with Probability Margin ACML 2011 A Potential-based Framework for Online Multi-class Learning with Partial Feedback AISTATS 2010 New Adaptive Algorithms for Online Classification NeurIPS 2010