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pro vyhledávání: '"Goodman, Erik"'
Experienced users often have useful knowledge and intuition in solving real-world optimization problems. User knowledge can be formulated as inter-variable relationships to assist an optimization algorithm in finding good solutions faster. Such inter
Externí odkaz:
http://arxiv.org/abs/2209.08604
"Innovization" is a task of learning common relationships among some or all of the Pareto-optimal (PO) solutions in multi- and many-objective optimization problems. Recent studies have shown that a chronological sequence of non-dominated solutions ob
Externí odkaz:
http://arxiv.org/abs/2011.10760
In this paper, we propose an efficient NAS algorithm for generating task-specific models that are competitive under multiple competing objectives. It comprises of two surrogates, one at the architecture level to improve sample efficiency and one at t
Externí odkaz:
http://arxiv.org/abs/2007.10396
Autor:
Lu, Zhichao, Sreekumar, Gautam, Goodman, Erik, Banzhaf, Wolfgang, Deb, Kalyanmoy, Boddeti, Vishnu Naresh
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
Neural architecture search (NAS) has emerged as a promising avenue for automatically designing task-specific neural networks. Existing NAS approaches require one complete search for each deployment specification of hardware or objective. This is a co
Externí odkaz:
http://arxiv.org/abs/2005.05859
Autor:
de Vega, Francisco Fernández, Olague, Gustavo, Chávez, Francisco, Lanza, Daniel, Banzhaf, Wolfgang, Goodman, Erik
Publikováno v:
Genetic Programming Theory and Practice XVII, 8 May 2020
The present and future of evolutionary algorithms depends on the proper use of modern parallel and distributed computing infrastructures. Although still sequential approaches dominate the landscape, available multi-core, many-core and distributed sys
Externí odkaz:
http://arxiv.org/abs/2005.00603
Publikováno v:
In Knowledge-Based Systems 25 October 2023 278
Autor:
Lu, Zhichao, Whalen, Ian, Dhebar, Yashesh, Deb, Kalyanmoy, Goodman, Erik, Banzhaf, Wolfgang, Boddeti, Vishnu Naresh
Early advancements in convolutional neural networks (CNNs) architectures are primarily driven by human expertise and by elaborate design processes. Recently, neural architecture search was proposed with the aim of automating the network design proces
Externí odkaz:
http://arxiv.org/abs/1912.01369
Autor:
Fan, Zhun, Li, Wenji, Wang, Zhaojun, Yuan, Yutong, Sun, Fuzan, Yang, Zhi, Ruan, Jie, Li, Zhaocheng, Goodman, Erik
This paper proposes a push and pull search method in the framework of differential evolution (PPS-DE) to solve constrained single-objective optimization problems (CSOPs). More specifically, two sub-populations, including the top and bottom sub-popula
Externí odkaz:
http://arxiv.org/abs/1812.06381
Autor:
Lu, Zhichao, Whalen, Ian, Boddeti, Vishnu, Dhebar, Yashesh, Deb, Kalyanmoy, Goodman, Erik, Banzhaf, Wolfgang
This paper introduces NSGA-Net -- an evolutionary approach for neural architecture search (NAS). NSGA-Net is designed with three goals in mind: (1) a procedure considering multiple and conflicting objectives, (2) an efficient procedure balancing expl
Externí odkaz:
http://arxiv.org/abs/1810.03522
Strabismus is one of the most influential ophthalmologic diseases in human's life. Timely detection of strabismus contributes to its prognosis and treatment. Telemedicine, which has great potential to alleviate the growing demand of the diagnosis of
Externí odkaz:
http://arxiv.org/abs/1809.02940