8 papers
Agentic High-Dimensional Bayesian Optimization with Hypothesis- and Evidence-Guided Search
Zhixuan Gao, Ke Xue, Rongxi Tan +2
High-dimensional Bayesian optimization (HDBO) seeks sample-efficient optimization when the number of variables is large relative to the evaluation budget. Recent LLM-based and agen…
Rethinking Learnability in Offline Data-driven Optimization
Chao Qian, Chen-Guang Wang, Rong-Xi Tan +1
Black-Box Optimization (BBO) has broad applications, while traditional algorithms such as evolutionary algorithms and Bayesian optimization face efficiency challenges as real-world…
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…
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…
BBOPlace-Bench: Benchmarking Black-Box Optimization for Chip Placement
Ke Xue, Ruo-Tong Chen, Rong-Xi Tan +5
Chip placement is a vital stage in modern chip design, and black-box optimization (BBO) has been applied to it for decades. Early BBO efforts, however, were limited by immature pro…
Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
Rong-Xi Tan, Ming Chen, Ke Xue +4
The pursuit of universal black-box optimization (BBO) algorithms is a longstanding goal. However, unlike domains such as language or vision, where scaling structured data has drive…
Offline Model-Based Optimization by Learning to Rank
Rong-Xi Tan, Ke Xue, Shen-Huan Lyu +5
Offline model-based optimization (MBO) aims to identify a design that maximizes a black-box function using only a fixed, pre-collected dataset of designs and their corresponding sc…
Offline Multi-Objective Optimization
Ke Xue, Rong-Xi Tan, Xiaobin Huang +1
Offline optimization aims to maximize a black-box objective function with a static dataset and has wide applications. In addition to the objective function being black-box and expe…