Summary of Sela: Tree-search Enhanced Llm Agents For Automated Machine Learning, by Yizhou Chi et al.
SELA: Tree-Search Enhanced LLM Agents for Automated Machine Learning
by Yizhou Chi, Yizhang Lin, Sirui Hong, Duyi Pan, Yaying Fei, Guanghao Mei, Bangbang Liu, Tianqi Pang, Jacky Kwok, Ceyao Zhang, Bang Liu, Chenglin Wu
First submitted to arxiv on: 22 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Machine Learning (cs.LG); Software Engineering (cs.SE)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces Tree-Search Enhanced LLM Agents (SELA), an innovative framework that leverages Monte Carlo Tree Search (MCTS) to optimize Automated Machine Learning (AutoML) processes. SELA represents pipeline configurations as trees, enabling agents to conduct experiments intelligently and iteratively refine their strategies, facilitating a more effective exploration of the machine learning solution space. The framework allows SELA to discover optimal pathways based on experimental feedback, improving the overall quality of the solutions. In an evaluation across 20 machine learning datasets, SELA achieves a win rate of 65% to 80% against each baseline, demonstrating its potential in tackling complex machine learning challenges. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper introduces a new way to help machines learn from data. Currently, machines can’t always find the best way to solve problems. The authors developed an innovative approach that uses tree search and feedback to improve the process of automating machine learning tasks. They tested their method on 20 different datasets and found that it performed better than other methods in many cases. This new approach could help machines learn more effectively and tackle complex problems. |
Keywords
* Artificial intelligence * Machine learning
