Journal ArticleDOI
Evolutionary deep learning: A survey
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In this paper , a large number of researches have proposed evolutionary deep learning (EDL) algorithms to optimize deep learning, so called EDL, which have obtained promising results.About:
This article is published in Neurocomputing.The article was published on 2022-02-01. It has received 60 citations till now. The article focuses on the topics: Computer science & Evolutionary algorithm.read more
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Journal ArticleDOI
A Review on Deep Learning Techniques for IoT Data
Kuruva Lakshmanna,Rajesh Kaluri,Nagaraja Gundluru,Zamil Alzamil,Dharmendra Singh Rajput,A. Khan,Mohd Anul Haq,Ahmed Alhussen +7 more
TL;DR: The increased amount of information gathered or produced is being used to further develop intelligence and application capabilities through Deep Learning techniques, and major reporting efforts for DL in the IoT region are surveyed and summarized.
Journal ArticleDOI
Quantum Behaved Particle Swarm Optimization-Based Deep Transfer Learning Model for Sugarcane Leaf Disease Detection and Classification
TL;DR: A quantum behaved particle swarm optimization based deep transfer learning (QBPSO-DTL) model for sugarcane leaf disease detection and classification which produces high accuracy and enhanced outcomes is presented.
Journal ArticleDOI
Distributed Differential Evolution With Adaptive Resource Allocation
TL;DR: A novel three-layer DDE framework with adaptive resource allocation (DDE-ARA), including the algorithm layer for evolving various differential evolution (DE) populations, the dispatch layer for dispatching the individuals in the DE populations to different distributed machines, and the machine layer for accommodating distributed computers is proposed.
Journal ArticleDOI
Distributed Differential Evolution With Adaptive Resource Allocation
TL;DR: In this paper , a three-layer DDE framework with adaptive resource allocation (DDE-ARA) is proposed, including the algorithm layer for evolving various differential evolution (DE) populations, the dispatch layer for dispatching the individuals in the DE populations to different distributed machines, and the machine layer for accommodating distributed computers.
Journal ArticleDOI
Dual Differential Grouping: A More General Decomposition Method for Large-Scale Optimization
TL;DR: This article makes the first attempt to decompose multiplicatively separable functions and proposes a novel method called dual DG (DDG) for better LSOP decomposition and optimization.
References
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Proceedings ArticleDOI
Deep Residual Learning for Image Recognition
TL;DR: In this article, the authors proposed a residual learning framework to ease the training of networks that are substantially deeper than those used previously, which won the 1st place on the ILSVRC 2015 classification task.
Journal ArticleDOI
Deep learning
TL;DR: Deep learning is making major advances in solving problems that have resisted the best attempts of the artificial intelligence community for many years, and will have many more successes in the near future because it requires very little engineering by hand and can easily take advantage of increases in the amount of available computation and data.
Book
Deep Learning
TL;DR: Deep learning as mentioned in this paper is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts, and it is used in many applications such as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames.
Journal ArticleDOI
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
Journal ArticleDOI
Mastering the game of Go with deep neural networks and tree search
David Silver,Aja Huang,Chris J. Maddison,Arthur Guez,Laurent Sifre,George van den Driessche,Julian Schrittwieser,Ioannis Antonoglou,Veda Panneershelvam,Marc Lanctot,Sander Dieleman,Dominik Grewe,John Nham,Nal Kalchbrenner,Ilya Sutskever,Timothy P. Lillicrap,Madeleine Leach,Koray Kavukcuoglu,Thore Graepel,Demis Hassabis +19 more
TL;DR: Using this search algorithm, the program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the human European Go champion by 5 games to 0.5, the first time that a computer program has defeated a human professional player in the full-sized game of Go.