double descent

High-Dimensional Analysis of Gradient Flow for Extensive-Width Quadratic Neural Networks JMLR 2026 Robust Predictive Uncertainty and Double Descent in Contaminated Bayesian Random Features UAI 2026 Analyzing the Role of Permutation Invariance in Linear Mode Connectivity AISTATS 2025 Asymptotics of Linear Regression with Linearly Dependent Data L4DC 2025 LoRA-MGPO: Mitigating Double Descent in Low-Rank Adaptation via Momentum-Guided Perturbation Optimization EMNLP 2025 Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression UAI 2024 DSD²: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free? AAAI 2024 Gibbs-Based Information Criteria and the Over-Parameterized Regime AISTATS 2024 Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise UAI 2024 Least Squares Regression Can Exhibit Under-Parameterized Double Descent NeurIPS 2024 Multiple Descent in the Multiple Random Feature Model JMLR 2024 On Double Descent in Reinforcement Learning with LSTD and Random Features ICLR 2024 On the Limitations of Fractal Dimension as a Measure of Generalization NeurIPS 2024 Post-Hoc Reversal: Are We Selecting Models Prematurely? NeurIPS 2024 Some Fundamental Aspects about Lipschitz Continuity of Neural Networks ICLR 2024 Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features ICML 2024 Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space ICLR 2024 A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning NeurIPS 2023 Bagging in overparameterized learning: Risk characterization and risk monotonization JMLR 2023 Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control NeurIPS 2023 Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles NeurIPS 2023 Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes ICML 2023 On double-descent in uncertainty quantification in overparametrized models AISTATS 2023 Optimal Activation Functions for the Random Features Regression Model ICLR 2023 Optimal Nonlinearities Improve Generalization Performance of Random Features ACML 2023