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An Information-Theoretic Framework for Unifying Active Learning Problems

An Information-Theoretic Framework for Unifying Active Learning Problems

19 December 2020
Q. Nguyen
Bryan Kian Hsiang Low
Patrick Jaillet
ArXivPDFHTML

Papers citing "An Information-Theoretic Framework for Unifying Active Learning Problems"

6 / 6 papers shown
Title
PIED: Physics-Informed Experimental Design for Inverse Problems
Apivich Hemachandra
Gregory Kang Ruey Lau
Szu Hui Ng
Bryan Kian Hsiang Low
PINN
76
0
0
10 Mar 2025
Max-value Entropy Search for Multi-Objective Bayesian Optimization with
  Constraints
Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints
Syrine Belakaria
Aryan Deshwal
J. Doppa
54
131
0
01 Sep 2020
Truncated Variance Reduction: A Unified Approach to Bayesian
  Optimization and Level-Set Estimation
Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation
Ilija Bogunovic
Jonathan Scarlett
Andreas Krause
Volkan Cevher
76
89
0
24 Oct 2016
Predictive Entropy Search for Efficient Global Optimization of Black-box
  Functions
Predictive Entropy Search for Efficient Global Optimization of Black-box Functions
José Miguel Hernández-Lobato
Matthew W. Hoffman
Zoubin Ghahramani
73
646
0
10 Jun 2014
Practical Bayesian Optimization of Machine Learning Algorithms
Practical Bayesian Optimization of Machine Learning Algorithms
Jasper Snoek
Hugo Larochelle
Ryan P. Adams
292
7,883
0
13 Jun 2012
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with
  Application to Active User Modeling and Hierarchical Reinforcement Learning
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning
E. Brochu
Vlad M. Cora
Nando de Freitas
GP
116
2,437
0
12 Dec 2010
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