risk bound

A Theory of the Risk for Optimization with Relaxation and its Application to Support Vector Machines JMLR 2021 Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models ICML 2021 On Empirical Risk Minimization with Dependent and Heavy-Tailed Data NeurIPS 2021 Prediction Under Latent Factor Regression: Adaptive PCR, Interpolating Predictors and Beyond JMLR 2021 Risk Bounds and Calibration for a Smart Predict-then-Optimize Method NeurIPS 2021 Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning ICML 2021 Risk Bounds for Over-parameterized Maximum Margin Classification on Sub-Gaussian Mixtures NeurIPS 2021 Risk Bounds for Unsupervised Cross-Domain Mapping with IPMs JMLR 2021 Scaling-Up Robust Gradient Descent Techniques AAAI 2021 Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$ NeurIPS 2021 Statistical guarantees for generative models without domination ALT 2021 Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher NeurIPS 2020 Risk Bounds for Learning Multiple Components with Permutation-Invariant Losses AISTATS 2020 Risk Bounds for Low Cost Bipartite Ranking UAI 2020 Risk Bounds for Reservoir Computing JMLR 2020 Second Order PAC-Bayesian Bounds for the Weighted Majority Vote NeurIPS 2020 Measurement Maximizing Adaptive Sampling with Risk Bounding Functions AAAI 2019 Risk Contours Map for Risk Bounded Motion Planning under Perception Uncertainties RSS 2019 Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate COLT 2019 Theoretical Analysis of Adversarial Learning: A Minimax Approach NeurIPS 2019 Theoretical Analysis of Label Distribution Learning AAAI 2019 ℓ_1-regression with Heavy-tailed Distributions NeurIPS 2018 Benefits from Superposed Hawkes Processes AISTATS 2018 Functional Gradient Boosting based on Residual Network Perception ICML 2018 Generalization Bounds for Uniformly Stable Algorithms NeurIPS 2018