excess risk

The Implicit Bias of Benign Overfitting JMLR 2023 Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty AISTATS 2023 Achieving Minimax Rates in Pool-Based Batch Active Learning ICML 2022 An Improper Estimator with Optimal Excess Risk in Misspecified Density Estimation and Logistic Regression JMLR 2022 Characterization of Excess Risk for Locally Strongly Convex Population Risk NeurIPS 2022 Foolish Crowds Support Benign Overfitting JMLR 2022 Label differential privacy via clustering AISTATS 2022 Near-optimal rate of consistency for linear models with missing values ICML 2022 Randomized Sketches for Clustering: Fast and Optimal Kernel k-Means NeurIPS 2022 Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime NeurIPS 2022 Spectral risk-based learning using unbounded losses AISTATS 2022 Statistical Learning and Inverse Problems: A Stochastic Gradient Approach NeurIPS 2022 The Interplay Between Implicit Bias and Benign Overfitting in Two-Layer Linear Networks JMLR 2022 Towards Understanding Generalization via Decomposing Excess Risk Dynamics ICLR 2022 Analyzing the tree-layer structure of Deep Forests ICML 2021 Benign Overfitting of Constant-Stepsize SGD for Linear Regression COLT 2021 Exponential Weights Algorithms for Selective Learning COLT 2021 Failures of Model-dependent Generalization Bounds for Least-norm Interpolation JMLR 2021 Fast Rates for Structured Prediction COLT 2021 Kernel-convoluted Deep Neural Networks with Data Augmentation AAAI 2021 Non-Euclidean Differentially Private Stochastic Convex Optimization COLT 2021 On Empirical Bayes Variational Autoencoder: An Excess Risk Bound COLT 2021 Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning ICML 2021 SGD Generalizes Better Than GD (And Regularization Doesn’t Help) COLT 2021 Sharper Generalization Bounds for Clustering ICML 2021