Research map / Learning theory and algorithms / Kernels and regression theory
Group Additive Structure Identification for Kernel Nonparametric Regression
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use exhaustive search with structure penalty (group complexity) vs. no penalty baseline | GASI group structure identification · Simulation M1-M5 | max identification frequency | Helped |
| Tune (mu, alpha) via validation set instead of picking best pair (ablation) | GASI exhaustive search · Simulation M1 | max identification frequency: 100 -> 59 | Hurt |
| Replace exhaustive search with backward stepwise search (ablation) | GASI group structure identification · Simulation M4 | max identification frequency: 100 -> 1 (exhaustive vs stepwise) | Hurt |
| Backward stepwise search instead of exhaustive search (ablation) | GASI group structure identification · Simulation M1-M3, M5 | max identification frequency | No clear effect |
Closest papers by meaning
- Group Sparse Additive Machine (NeurIPS 2017 · similarity 0.88)
- Bayesian Additive Distribution Regression (NeurIPS 2026 · similarity 0.83)
- Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$ (ICML 2025 · similarity 0.83)
- Learning with Exact Invariances in Polynomial Time (ICML 2025 · similarity 0.83)
- Kernel Regression in Structured Non-IID Settings: Theory and Implications for Denoising Score Learning (NeurIPS 2025 · similarity 0.82)
- High-Dimensional Tensor Regression With Oracle Properties (ICML 2025 · similarity 0.82)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.