concentration inequality

Risk Monotonicity in Statistical Learning NeurIPS 2021 A nonasymptotic law of iterated logarithm for general M-estimators AISTATS 2020 Best Arm Identification for Cascading Bandits in the Fixed Confidence Setting ICML 2020 On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration COLT 2020 PAC-Bayesian Bound for the Conditional Value at Risk NeurIPS 2020 Sharper Bounds for Uniformly Stable Algorithms COLT 2020 Tightening Exploration in Upper Confidence Reinforcement Learning ICML 2020 Uncertainty Quantification for Inferring Hawkes Networks NeurIPS 2020 A Kernel Multiple Change-point Algorithm via Model Selection JMLR 2019 An Exponential Tail Bound for the Deleted Estimate AAAI 2019 Best Arm Identification for Contaminated Bandits JMLR 2019 Concentration Inequalities for Conditional Value at Risk ICML 2019 McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds NeurIPS 2019 Optimal Best Markovian Arm Identification with Fixed Confidence NeurIPS 2019 PAC-Bayes under potentially heavy tails NeurIPS 2019 PAC-Bayes Un-Expected Bernstein Inequality NeurIPS 2019 Uniform concentration and symmetrization for weak interactions COLT 2019 Concentration inequalities for empirical processes of linear time series JMLR 2018 Data-Dependent Stability of Stochastic Gradient Descent ICML 2018 Theoretical Analysis of Cross-Validation for Estimating the Risk of the k-Nearest Neighbor Classifier JMLR 2018 Boundary Crossing for General Exponential Families ALT 2017 Learning from Networked Examples ALT 2017 Minimax Regret Bounds for Reinforcement Learning ICML 2017 Optimistic Planning for the Stochastic Knapsack Problem AISTATS 2017 Adaptive Concentration Inequalities for Sequential Decision Problems NeurIPS 2016