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ridge regression

134 papers

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Also known as

MRR RR

Co-occurring keywords

kernel methods (1096) linear regression (281) lasso regression (61) reproducing kernel hilbert space (334) regret bound (1918) high-dimensional regression (142) implicit regularization (93) least square (100) ordinary least square (15) logistic regression (382)

Papers

FUSE : A Ridge and Random Forest-Based Metric for Evaluating MT in Indigenous Languages NAACL 2025
RRInf: Efficient Influence Function Estimation via Ridge Regression for Large Language Models and Text-to-Image Diffusion Models EMNLP 2025
ProKeR: A Kernel Perspective on Few-Shot Adaptation of Large Vision-Language Models CVPR 2025
The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective JMLR 2024
The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems NIPS 2024
Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm JMLR 2024
UPN-ICC at BEA 2024 Shared Task: Leveraging LLMs for Multiple-Choice Questions Difficulty Prediction NAACL 2024
Advancing Cross-domain Discriminability in Continual Learning of Vision-Language Models NIPS 2024
In-Context Learning with Representations: Contextual Generalization of Trained Transformers NIPS 2024
High-Dimensional Analysis for Generalized Nonlinear Regression: From Asymptotics to Algorithm AAAI 2024
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality NIPS 2024
Low-Rank Approximation of Structural Redundancy for Self-Supervised Learning CLEAR 2024
Dimension-free deterministic equivalents and scaling laws for random feature regression NIPS 2024
Multiple Descent in the Multiple Random Feature Model JMLR 2024
Elastic Gradient Descent, an Iterative Optimization Method Approximating the Solution Paths of the Elastic Net JMLR 2023
Benign overfitting in ridge regression JMLR 2023
The Implicit Regularization of Momentum Gradient Descent in Overparametrized Models AAAI 2023
Francis Bacon at SemEval-2023 Task 4: Ensembling BERT and GloVe for Value Identification in Arguments SEMEVAL 2023
Reward Imputation with Sketching for Contextual Batched Bandits NIPS 2023
Naive imputation implicitly regularizes high-dimensional linear models ICML 2023
Bayes-optimal Learning of Deep Random Networks of Extensive-width ICML 2023
Revisiting minimum description length complexity in overparameterized models JMLR 2023
Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection NIPS 2023
Bayes beats Cross Validation: Efficient and Accurate Ridge Regression via Expectation Maximization NIPS 2023
Deterministic equivalent and error universality of deep random features learning ICML 2023