Linda Cai

2 accepted papers

2026

Cost-aware Stopping for Bayesian Optimization

Qian Xie, Linda Cai, Alexander Terenin, Peter Frazier, Ziv Scully

ICML 2026poster

In automated machine learning, scientific discovery, and other applications of Bayesian optimization, deciding when to stop evaluating expensive black-box functions in a cost-aware manner is an important but underexplored practical consideration. A natural performance metric for this purpose is the …

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2025

Faster Diffusion Sampling with Randomized Midpoints: Sequential and Parallel

Shivam Gupta, Linda Cai, Sitan Chen

ICLR 2025poster

Sampling algorithms play an important role in controlling the quality and runtime of diffusion model inference. In recent years, a number of works (Chen et al., 2023c;b; Benton et al., 2023; Lee et al., 2022) have analyzed algorithms for diffusion sampling with provable guarantees; these works show…

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