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Bilevel Optimization by Conditional Bayesian Optimization
Bilevel optimization problems have two decision-makers: a leader and a follower (sometimes more than one of either, or both). The leader must solve a constrained optimization problem in which some decisions are made by the follower. These problems are much harder to solve than those with a single decision-maker, and efficient optimal algorithms are ...
Vedat Dogan, Steven Prestwich
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Advanced Healthcare Materials, EarlyView.We developed a micro‐sized, biocompatible implant for postoperative sustained delivery of anti‐fibrotic antibodies in glaucoma surgery. Machine learning‐guided optimization of polymer composition, implant geometry, and porosity enabled precise control of drug release.
Mengqi Qin +5 more
wiley +1 more source
Bayesian Optimization with Unknown Constraints [PDF]
, 2014 Recent work on Bayesian optimization has shown its effectiveness in global optimization of difficult black-box objective functions. Many real-world optimization problems of interest also have constraints which are unknown a priori.
Adams, Ryan P. +2 more
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, 2022 Bayesian optimization (BO) is a powerful approach to sample-efficient optimization of black-box objective functions. However, the application of BO to areas such as recommendation systems often requires taking the interpretability and simplicity of the configurations into consideration, a setting that has not been previously studied in the BO ...
Liu, Sulin +4 more
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Advanced Materials, EarlyView.Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu +3 more
wiley +1 more source
Advanced Materials, EarlyView.Electrochemical CO2RR is a key technology for converting CO2 into chemicals, but there remains a gap between “laboratory science” and “engineering practice” in current research. This review establishes a multi‐scale research framework, encompassing atomic‐level characterization, microenvironment regulation, external field‐assisted optimization, and AI ...
Ping Hong +3 more
wiley +1 more source
Advanced Materials, EarlyView.A machine learning‐guided bio‐interfacial design strategy resolves the long‐standing strength–toughness–functionality trade‐off in nanocomposites. By efficiently mapping high‐performance regions in the composition–processing space, the approach delivers hierarchically entangled, nanosheet‐pinned architectures that combine mechanical robustness ...
Hao Wang +10 more
wiley +1 more source
Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)Lung cancer's high mortality rate makes early detection crucial. Machine learning techniques, especially convolutional neural networks (CNN), play a very important role in lung nodule detection.
Kadek Eka Sapta Wijaya +2 more
doaj +1 more source
Active Bayesian Optimization: Minimizing Minimizer Entropy [PDF]
, 2012 The ultimate goal of optimization is to find the minimizer of a target function.However, typical criteria for active optimization often ignore the uncertainty about the minimizer.
Nassar, Marcel +2 more
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