[HTML][HTML] Automating the design-build-test-learn cycle towards next-generation bacterial cell factories
Automation is playing an increasingly significant role in synthetic biology. Groundbreaking
technologies, developed over the past 20 years, have enormously accelerated the …
technologies, developed over the past 20 years, have enormously accelerated the …
Derivative-free optimization methods
In many optimization problems arising from scientific, engineering and artificial intelligence
applications, objective and constraint functions are available only as the output of a black …
applications, objective and constraint functions are available only as the output of a black …
[图书][B] Introduction: tools and challenges in derivative-free and blackbox optimization
In this introductory chapter, we present a high-level description of optimization, blackbox
optimization, and derivative-free optimization. We introduce some basic optimization …
optimization, and derivative-free optimization. We introduce some basic optimization …
Review and comparison of algorithms and software for mixed-integer derivative-free optimization
N Ploskas, NV Sahinidis - Journal of Global Optimization, 2022 - Springer
This paper reviews the literature on algorithms for solving bound-constrained mixed-integer
derivative-free optimization problems and presents a systematic comparison of available …
derivative-free optimization problems and presents a systematic comparison of available …
Improving the flexibility and robustness of model-based derivative-free optimization solvers
We present two software packages for derivative-free optimization (DFO): DFO-LS for
nonlinear least-squares problems and Py-BOBYQA for general objectives, both with optional …
nonlinear least-squares problems and Py-BOBYQA for general objectives, both with optional …
PDFO: a cross-platform package for Powell's derivative-free optimization solvers
TM Ragonneau, Z Zhang - Mathematical Programming Computation, 2024 - Springer
Abstract The late Professor MJD Powell devised five trust-region methods for derivative-free
optimization, namely COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. He carefully …
optimization, namely COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. He carefully …
[图书][B] Evaluation Complexity of Algorithms for Nonconvex Optimization: Theory, Computation and Perspectives
Do you know the difference between an optimist and a pessimist? The former believes we
live in the best possible world, and the latter is afraid that the former might be right.… In that …
live in the best possible world, and the latter is afraid that the former might be right.… In that …
The mesh adaptive direct search algorithm for granular and discrete variables
C Audet, S Le Digabel, C Tribes - SIAM Journal on Optimization, 2019 - SIAM
The mesh adaptive direct search (Mads) algorithm is designed for blackbox optimization
problems for which the functions defining the objective and the constraints are typically the …
problems for which the functions defining the objective and the constraints are typically the …
HyperNOMAD: Hyperparameter optimization of deep neural networks using mesh adaptive direct search
D Lakhmiri, SL Digabel, C Tribes - ACM Transactions on Mathematical …, 2021 - dl.acm.org
The performance of deep neural networks is highly sensitive to the choice of the
hyperparameters that define the structure of the network and the learning process. When …
hyperparameters that define the structure of the network and the learning process. When …
Model-based derivative-free optimization methods and software
TM Ragonneau - arXiv preprint arXiv:2210.12018, 2022 - arxiv.org
This thesis studies derivative-free optimization (DFO), particularly model-based methods
and software. These methods are motivated by optimization problems for which it is …
and software. These methods are motivated by optimization problems for which it is …