excess risk bound

Beyond Heuristic Prompting: A Concept-Guided Bayesian Framework for Zero-Shot Image Recognition CVPR 2026 Classification Under Local Differential Privacy with Model Reversal and Model Averaging JMLR 2026 Enhancing Kernel Power K-means: Scalable and Robust Clustering with Random Fourier Features and Possibilistic Method AAAI 2026 On-Average Stability of Multipass Preconditioned SGD and Effective Dimension COLT 2026 Adaptive Estimation and Learning under Temporal Distribution Shift ICML 2025 A New Concentration Inequality for Sampling Without Replacement and Its Application for Transductive Learning ICML 2025 On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes JMLR 2025 A Statistical Framework for Data-dependent Retrieval-Augmented Models ICML 2024 Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition JMLR 2024 Learning with a linear loss function: excess risk and estimation bounds for ERM, minmax MOM and their regularized versions with applications to robustness in sparse PCA. JMLR 2024 Minimum-Norm Interpolation Under Covariate Shift ICML 2024 Nonparametric Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks JMLR 2024 Risk Bounds of Accelerated SGD for Overparameterized Linear Regression ICLR 2024 Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels AISTATS 2024 Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms ICML 2024 Towards Sharper Risk Bounds for Minimax Problems IJCAI 2024 A Statistical Learning Take on the Concordance Index for Survival Analysis AISTATS 2023 Deep linear networks can benignly overfit when shallow ones do JMLR 2023 Fast Excess Risk Rates via Offset Rademacher Complexity ICML 2023 Optimal Excess Risk Bounds for Empirical Risk Minimization on p-Norm Linear Regression NeurIPS 2023 Understanding the Generalization Performance of Spectral Clustering Algorithms AAAI 2023 Approximation with CNNs in Sobolev Space: with Applications to Classification NeurIPS 2022 Improved Fine-Tuning by Better Leveraging Pre-Training Data NeurIPS 2022 Interpolating Predictors in High-Dimensional Factor Regression JMLR 2022 Learning with little mixing NeurIPS 2022