Results 11 to 20 of about 226,052 (275)
Optimizing Designs Containing Black Boxes [PDF]
Proceedings of the 34th Design Automation Conference, 1997 We define a notion of equivalence for designs containingblack boxes i.e., components whose functionality is notknown; these arise naturally in the course of hierarchicaldesign. Using this notion, we describe a sound andcomplete methodology for optimizing such designs.
Tai-Hung Liu +3 more
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Versatile black-box optimization [PDF]
Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 2020 Accepted at GECCO ...
Liu, Jialin +6 more
openaire +3 more sources
MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning [PDF]
Neural Information Processing Systems, 2023 Recently, Meta-Black-Box Optimization with Reinforcement Learning (MetaBBO-RL) has showcased the power of leveraging RL at the meta-level to mitigate manual fine-tuning of low-level black-box optimizers.
Zeyuan Ma +7 more
semanticscholar +1 more source
High-dimensional black-box optimization under uncertainty [PDF]
Computers & Operations Research, 2022 Optimizing expensive black-box systems with limited data is an extremely challenging problem. As a resolution, we present a new surrogate optimization approach by addressing two gaps in prior research -- unimportant input variables and inefficient treatment of uncertainty associated with the black-box output.
Anahideh, Hadis +2 more
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Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization [PDF]
Annual Conference on Genetic and Evolutionary Computation, 2023 Genetic algorithms constitute a family of black-box optimization algorithms, which take inspiration from the principles of biological evolution. While they provide a general-purpose tool for optimization, their particular instantiations can be heuristic ...
R. Lange +6 more
semanticscholar +1 more source
Discovering representations for black-box optimization [PDF]
Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 2020 The encoding of solutions in black-box optimization is a delicate, handcrafted balance between expressiveness and domain knowledge -- between exploring a wide variety of solutions, and ensuring that those solutions are useful. Our main insight is that this process can be automated by generating a dataset of high-performing solutions with a quality ...
Gaier, Adam +2 more
openaire +3 more sources
Macro Placement by Wire-Mask-Guided Black-Box Optimization [PDF]
Neural Information Processing Systems, 2023 The development of very large-scale integration (VLSI) technology has posed new challenges for electronic design automation (EDA) techniques in chip floorplanning.
Yunqi Shi +3 more
semanticscholar +1 more source
B2Opt: Learning to Optimize Black-box Optimization with Little Budget [PDF]
AAAI Conference on Artificial Intelligence, 2023 The core challenge of high-dimensional and expensive black-box optimization (BBO) is how to obtain better performance faster with little function evaluation cost.
Xiaobin Li +4 more
semanticscholar +1 more source
Mathematics, 2023 In order to overcome the drawbacks of expensive function evaluation in the practical reliability-based design optimization (RBDO) problem, researchers have proposed the black box-based RBDO method.
Li Lu, Yizhong Wu, Qi Zhang, Ping Qiao
doaj +1 more source
OpenBox: A Python Toolkit for Generalized Black-box Optimization [PDF]
Journal of machine learning research, 2023 Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, experimental design, and database knob tuning. However, users still face challenges when applying BBO methods to their problems at hand with existing ...
Huaijun Jiang +5 more
semanticscholar +1 more source