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double descent

52 papers

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Co-occurring keywords

generalization error (285) neural network (6616) random feature (89) neural network optimization (1293) ensemble learning (1271) ridge regression (134) high-dimensional regression (142) linear regression (281) kernel methods (1096) random matrix theory (63)

Papers

LoRA-MGPO: Mitigating Double Descent in Low-Rank Adaptation via Momentum-Guided Perturbation Optimization EMNLP 2025
Least Squares Regression Can Exhibit Under-Parameterized Double Descent NIPS 2024
Post-Hoc Reversal: Are We Selecting Models Prematurely? NIPS 2024
Multiple Descent in the Multiple Random Feature Model JMLR 2024
Gibbs-Based Information Criteria and the Over-Parameterized Regime AISTATS 2024
On the Limitations of Fractal Dimension as a Measure of Generalization NIPS 2024
DSD²: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free? AAAI 2024
On double-descent in uncertainty quantification in overparametrized models AISTATS 2023
A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning NIPS 2023
Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles NIPS 2023
Optimal Nonlinearities Improve Generalization Performance of Random Features ACML 2023
Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control NIPS 2023
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes ICML 2023
Bagging in overparameterized learning: Risk characterization and risk monotonization JMLR 2023
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent From the Decision Boundary Perspective CVPR 2022
On the Double Descent of Random Features Models Trained with SGD NIPS 2022
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting NIPS 2022
Ridgeless Regression with Random Features IJCAI 2022
Sparse Double Descent: Where Network Pruning Aggravates Overfitting ICML 2022
Information bottleneck theory of high-dimensional regression: relevancy, efficiency and optimality NIPS 2022
Multi-scale Feature Learning Dynamics: Insights for Double Descent ICML 2022
Target alignment in truncated kernel ridge regression NIPS 2022
RIGA at SemEval-2022 Task 1: Scaling Recurrent Neural Networks for CODWOE Dictionary Modeling SEMEVAL 2022
RIGA at SemEval-2022 Task 1: Scaling Recurrent Neural Networks for CODWOE Dictionary Modeling NAACL 2022
Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension ICML 2022