Research map / Learning theory and algorithms / Kernels and regression theory
An Iterative, Sketching-based Framework for Ridge Regression
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| increase number of iterations of the sketched ridge regression algorithm | Iterative sketching ridge regression · ARCENE | relative solution error | Helped |
| increase regularization lambda (lower degrees of freedom d_lambda) (ablation) | Iterative sketching ridge regression · ARCENE | relative solution error | Helped |
| sample columns by ridge leverage scores instead of uniform or leverage scores (ablation) | Iterative sketching ridge regression · ARCENE | relative solution error | Helped |
Closest papers by meaning
- Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging (ICML 2017 · similarity 0.93)
- Ridge Regression: Structure, Cross-Validation, and Sketching (ICLR 2020 · similarity 0.93)
- Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning (ICLR 2024 · similarity 0.89)
- Distributed Least Squares in Small Space via Sketching and Bias Reduction (NeurIPS 2024 · similarity 0.88)
- The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems (NeurIPS 2024 · similarity 0.87)
- Risk and cross validation in ridge regression with correlated samples (ICML 2025 · similarity 0.86)
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