3 papers
cs.LG2026
On the Learnability of Offline Model-Based Optimization: A Ranking Perspective
Shen-Huan Lyu, Rong-Xi Tan, Ke Xue +4
Offline model-based optimization (MBO) seeks to discover high-performing designs using only a fixed dataset of past evaluations. Most existing methods rely on learning a surrogate…
cs.LG2025
Beyond Token-level Supervision: Unlocking the Potential of Decoding-based Regression via Reinforcement Learning
Ming Chen, Sheng Tang, Rong-Xi Tan +4
Decoding-based regression, which reformulates regression as a sequence generation task, has emerged as a promising paradigm of applying large language models for numerical predicti…
cs.LG2025
Sequential Multi-Agent Dynamic Algorithm Configuration
Chen Lu, Ke Xue, Lei Yuan +4
Dynamic algorithm configuration (DAC) is a recent trend in automated machine learning, which can dynamically adjust the algorithm's configuration during the execution process and r…