heavy-tailed data

Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates AAAI 2025 t^3-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence ICLR 2024 Differentially Private Stochastic Convex Optimization in (Non)-Euclidean Space Revisited UAI 2023 Online robust non-stationary estimation NeurIPS 2023 Anytime Guarantees under Heavy-Tailed Data AAAI 2022 Improved Rates for Differentially Private Stochastic Convex Optimization with Heavy-Tailed Data ICML 2022 Marginal Tail-Adaptive Normalizing Flows ICML 2022 Private Stochastic Convex Optimization and Sparse Learning with Heavy-tailed Data Revisited IJCAI 2022 Stochastic linear optimization never overfits with quadratically-bounded losses on general data COLT 2022 On Empirical Risk Minimization with Dependent and Heavy-Tailed Data NeurIPS 2021 On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data ICML 2020 Better generalization with less data using robust gradient descent ICML 2019 Globally Optimal Learning for Structured Elliptical Losses NeurIPS 2019 On the statistical rate of nonlinear recovery in generative models with heavy-tailed data ICML 2019