Research map / Learning theory and algorithms / Prediction and decision losses
Feature Learning for Interpretable, Performant Decision Trees
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.
Closest papers by meaning
- Multistage Defer Trees for Hybrid Interpretability: If at First You Can't Succeed, Tree Again (NeurIPS 2026 · similarity 0.90)
- Near-Optimal Decision Trees in a SPLIT Second (ICML 2025 · similarity 0.89)
- Leveraging Predictive Equivalence in Decision Trees (ICML 2025 · similarity 0.89)
- Generative Model for Decision Trees (AAAI 2024 · similarity 0.88)
- Branches: Efficiently Seeking Optimal Sparse Decision Trees via AO* (ICML 2025 · similarity 0.87)
- Learning Small Decision Trees with Few Outliers: A Parameterized Perspective (AAAI 2024 · similarity 0.87)
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.