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Sample-Then-Optimize Batch Neural Thompson Sampling
13 October 2022
Zhongxiang Dai
Yao Shu
Bryan Kian Hsiang Low
P. Jaillet
AAML
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Papers citing
"Sample-Then-Optimize Batch Neural Thompson Sampling"
8 / 8 papers shown
Title
Batched Bayesian optimization by maximizing the probability of including the optimum
Jenna C. Fromer
Runzhong Wang
Mrunali Manjrekar
Austin Tripp
José Miguel Hernández-Lobato
Connor W. Coley
47
0
0
08 Oct 2024
Graph Neural Thompson Sampling
Shuang Wu
Arash A. Amini
45
0
0
15 Jun 2024
Robustifying and Boosting Training-Free Neural Architecture Search
Zhenfeng He
Yao Shu
Zhongxiang Dai
K. H. Low
32
1
0
12 Mar 2024
Training-Free Neural Active Learning with Initialization-Robustness Guarantees
Apivich Hemachandra
Zhongxiang Dai
Jasraj Singh
See-Kiong Ng
K. H. Low
AAML
33
6
0
07 Jun 2023
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search
Yao Shu
Zhongxiang Dai
Zhaoxuan Wu
K. H. Low
AI4CE
46
24
0
24 Jan 2022
Gaussian Process Bandit Optimization with Few Batches
Zihan Li
Jonathan Scarlett
GP
123
47
0
15 Oct 2021
Federated Bayesian Optimization via Thompson Sampling
Zhongxiang Dai
K. H. Low
Patrick Jaillet
FedML
86
109
0
20 Oct 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
273
5,660
0
05 Dec 2016
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