heavy-tailed distribution

A Robust Univariate Mean Estimator is All You Need AISTATS 2020 Concentration bounds for CVaR estimation: The cases of light-tailed and heavy-tailed distributions ICML 2020 Cooperative Multi-Agent Bandits with Heavy Tails ICML 2020 Fast Rates for General Unbounded Loss Functions: From ERM to Generalized Bayes JMLR 2020 List-Decodable Mean Estimation via Iterative Multi-Filtering NeurIPS 2020 Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs IJCAI 2020 Optimal $δ$-Correct Best-Arm Selection for Heavy-Tailed Distributions ALT 2020 Private Mean Estimation of Heavy-Tailed Distributions COLT 2020 Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization NeurIPS 2020 Stochastic bandits with arm-dependent delays ICML 2020 Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping NeurIPS 2020 Affine Invariant Covariance Estimation for Heavy-Tailed Distributions COLT 2019 A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks ICML 2019 Bayesian Optimization under Heavy-tailed Payoffs NeurIPS 2019 Cross-sectional Learning of Extremal Dependence among Financial Assets NeurIPS 2019 Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards NeurIPS 2019 First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise NeurIPS 2019 Thompson Sampling on Symmetric Alpha-Stable Bandits IJCAI 2019 Understanding Priors in Bayesian Neural Networks at the Unit Level ICML 2019 ℓ_1-regression with Heavy-tailed Distributions NeurIPS 2018 Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs NeurIPS 2018 Local Minima, Heavy Tails, and Search Effort for GBFS IJCAI 2018 Estimation of the covariance structure of heavy-tailed distributions NeurIPS 2017 Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for Markov Chain Monte Carlo ICML 2017 Fast learning rates with heavy-tailed losses NeurIPS 2016