65 citations · 128 across the 12 of their papers we have counts for
6 papers · 1 filter
See it to Place it: Evolving Macro Placements with Vision-Language Models
Ikechukwu Uchendu, Swati Goel, Karly Hou +5
We propose using Vision-Language Models (VLMs) for macro placement in chip floorplanning, a complex optimization task that has recently shown promising advancements through machine…
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes
Yunyue Wei, Vincent Zhuang, Saraswati Soedarmadji +1
Bayesian optimization is an effective technique for black-box optimization, but its applicability is typically limited to low-dimensional and small-budget problems due to the cubic…
Training Language Models to Self-Correct via Reinforcement Learning
Aviral Kumar, Vincent Zhuang, Rishabh Agarwal +15
Self-correction is a highly desirable capability of large language models (LLMs), yet it has consistently been found to be largely ineffective in modern LLMs. Current methods for t…
No-Regret Reinforcement Learning with Heavy-Tailed Rewards
Vincent Zhuang, Yanan Sui
Reinforcement learning algorithms typically assume rewards to be sampled from light-tailed distributions, such as Gaussian or bounded. However, a wide variety of real-world systems…
Stagewise Safe Bayesian Optimization with Gaussian Processes
Yanan Sui, Vincent Zhuang, Joel W. Burdick +1
Enforcing safety is a key aspect of many problems pertaining to sequential decision making under uncertainty, which require the decisions made at every step to be both informative…
Multi-dueling Bandits with Dependent Arms
Yanan Sui, Vincent Zhuang, Joel W. Burdick +1
The dueling bandits problem is an online learning framework for learning from pairwise preference feedback, and is particularly well-suited for modeling settings that elicit subjec…