overparameterized model

Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity NeurIPS 2022 How catastrophic can catastrophic forgetting be in linear regression? COLT 2022 Memorize to generalize: on the necessity of interpolation in high dimensional linear regression COLT 2022 Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently NeurIPS 2022 Principal Components Bias in Over-parameterized Linear Models, and its Manifestation in Deep Neural Networks JMLR 2022 The alignment property of SGD noise and how it helps select flat minima: A stability analysis NeurIPS 2022 UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup NeurIPS 2022 Understanding Benign Overfitting in Gradient-Based Meta Learning NeurIPS 2022 Asymptotics of Ridge(less) Regression under General Source Condition AISTATS 2021 Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification ICLR 2021 Characterizing Structural Regularities of Labeled Data in Overparameterized Models ICML 2021 Failures of Model-dependent Generalization Bounds for Least-norm Interpolation JMLR 2021 Good Classifiers are Abundant in the Interpolating Regime AISTATS 2021 Offline Contextual Bandits with Overparameterized Models ICML 2021 On Statistical Bias In Active Learning: How and When to Fix It ICLR 2021 On the Minimal Error of Empirical Risk Minimization COLT 2021 SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs NeurIPS 2021 Shape Matters: Understanding the Implicit Bias of the Noise Covariance COLT 2021 Sharpness-aware Minimization for Efficiently Improving Generalization ICLR 2021 Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction NeurIPS 2021 Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence AISTATS 2021 Training Over-parameterized Models with Non-decomposable Objectives NeurIPS 2021 Understanding the Dynamics of Gradient Flow in Overparameterized Linear models ICML 2021 Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation ICML 2020 Rethinking Bias-Variance Trade-off for Generalization of Neural Networks ICML 2020