risk bound

Bridging Domain Invariance and Diversity: A Fine-Grained Risk Bound for Domain Generalization JMLR 2026 Optimization and Generalization of Gradient Descent for Shallow ReLU Networks with Minimal Width JMLR 2026 SPoRt - Safe Policy Ratio: Certified Training and Deployment of Task Policies in Model-Free RL IJCAI 2025 Credal Learning Theory NeurIPS 2024 Minimax Linear Regression under the Quantile Risk COLT 2024 On the Provable Advantage of Unsupervised Pretraining ICLR 2024 Safeguarded Progress in Reinforcement Learning: Safe Bayesian Exploration for Control Policy Synthesis AAAI 2024 Benign Overfitting in Adversarially Robust Linear Classification UAI 2023 Benign Overfitting in Two-layer ReLU Convolutional Neural Networks ICML 2023 Erratum: Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm JMLR 2023 Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron ICML 2023 Local Risk Bounds for Statistical Aggregation COLT 2023 Minimum-Risk Recalibration of Classifiers NeurIPS 2023 Risk Bounds for Positive-Unlabeled Learning Under the Selected At Random Assumption JMLR 2023 Risk Bounds on Aleatoric Uncertainty Recovery AISTATS 2023 Selective Nonparametric Regression via Testing ACML 2023 Tight Risk Bounds for Gradient Descent on Separable Data NeurIPS 2023 Topology-aware Robust Optimization for Out-of-Distribution Generalization ICLR 2023 Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space NeurIPS 2022 Last Iterate Risk Bounds of SGD with Decaying Stepsize for Overparameterized Linear Regression ICML 2022 Randomized Sketches for Clustering: Fast and Optimal Kernel k-Means NeurIPS 2022 Risk bounds for aggregated shallow neural networks using Gaussian priors COLT 2022 SCRIB: Set-Classifier with Class-Specific Risk Bounds for Blackbox Models AAAI 2022 Statistical Learning and Inverse Problems: A Stochastic Gradient Approach NeurIPS 2022 Analyzing the tree-layer structure of Deep Forests ICML 2021