mlsanityData to 7 Oct 2026

TS-RSR: A provably efficient approach for batch Bayesian Optimization

arXiv 2403.04764 ↗First posted 7 Mar 2024cs.LG math.OC stat.MLcited by 4

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Abstract (arXiv)

This paper presents a new approach for batch Bayesian Optimization (BO) called Thompson Sampling-Regret to Sigma Ratio directed sampling (TS-RSR), where we sample a new batch of actions by minimizing a Thompson Sampling approximation of a regret to uncertainty ratio. Our sampling objective is able to coordinate the actions chosen in each batch in a way that minimizes redundancy between points whilst focusing on points with high predictive means or high uncertainty. Theoretically, we provide rigorous convergence guarantees on our algorithm's regret, and numerically, we demonstrate that our method attains state-of-the-art performance on a range of challenging synthetic and realistic test functions, where it outperforms several competitive benchmark batch BO algorithms.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 24 of its 39 references that are in the map. First posted on arXiv 7 Mar 2024.

Builds on

24 of 39 references.

References · 24

  1. 2018A Tutorial on Bayesian Optimizationcited by 734
  2. 2017Max-value Entropy Search for Efficient Bayesian Optimizationcited by 202
  3. 2014Learning to Optimize via Information-Directed Samplingcited by 168
  4. 2020On Information Gain and Regret Bounds in Gaussian Process Banditscited by 156
  5. 2023Unexpected Improvements to Expected Improvement for Bayesian Optimizationcited by 144
  6. 2015Batch Bayesian Optimization via Local Penalizationcited by 103
  7. 2017Constrained Bayesian Optimization with Noisy Experimentscited by 103
  8. 2020Federated Bayesian Optimization via Thompson Samplingcited by 77
  9. 2017Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Spacecited by 76
  10. 2018Information Directed Sampling and Bandits with Heteroscedastic Noisecited by 75
  11. 2022Joint Entropy Search for Maximally-Informed Bayesian Optimizationcited by 55
  12. 2015Predictive Entropy Search for Bayesian Optimization with Unknown Constraintscited by 51
12 more
  1. 2013Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Explorationcited by 50
  2. 2015Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functionscited by 31
  3. 2016Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraintscited by 27
  4. 2021Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processescited by 23
  5. 2015Optimization as Estimation with Gaussian Processes in Bandit Settingscited by 17
  6. 2019On Batch Bayesian Optimizationcited by 12
  7. 2022Bayesian Optimization under Stochastic Delayed Feedbackcited by 10
  8. 2019Fully Distributed Bayesian Optimization with Stochastic Policiescited by 9
  9. 2023SOBER: Highly Parallel Bayesian Optimization and Bayesian Quadrature over Discrete and Mixed Spacescited by 7
  10. 2023Gaussian Max-Value Entropy Search for Multi-Agent Bayesian Optimizationcited by 7
  11. 2020TS-UCB: Improving on Thompson Sampling With Little to No Additional Computationcited by 6
  12. 2019Sampling Acquisition Functions for Batch Bayesian Optimizationcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 0; 2026: 2.

4 papers.

  1. 2024Batched Bayesian optimization by maximizing the probability of including the optimumcited by 2
  2. 2024Distributed Thompson sampling under constrained communicationcited by 2
  3. 2026D-IMPL: A Diffusion-based Solver for Parameterized BBOscited by 0
  4. 2026Collaborative Principle Evolution via Evidence Transfer for Scientific Discoverycited by 0