LEADER 03858nam 2200901z- 450 001 9910557610303321 005 20231214132851.0 035 $a(CKB)5400000000045299 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/79633 035 $a(EXLCZ)995400000000045299 100 $a20202203d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputational Optimizations for Machine Learning 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 electronic resource (276 p.) 311 $a3-0365-3186-6 311 $a3-0365-3187-4 330 $aThe present book contains the 10 articles finally accepted for publication in the Special Issue ?Computational Optimizations for Machine Learning? of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory and applications of machine learning, neural networks and artificial intelligence. These topics include, among others, various types of machine learning classes, such as supervised, unsupervised and reinforcement learning, deep neural networks, convolutional neural networks, GANs, decision trees, linear regression, SVM, K-means clustering, Q-learning, temporal difference, deep adversarial networks and more. It is hoped that the book will be interesting and useful to those developing mathematical algorithms and applications in the domain of artificial intelligence and machine learning as well as for those having the appropriate mathematical background and willing to become familiar with recent advances of machine learning computational optimization mathematics, which has nowadays permeated into almost all sectors of human life and activity. 606 $aResearch & information: general$2bicssc 606 $aMathematics & science$2bicssc 610 $aARIMA model 610 $atime series analysis 610 $aonline optimization 610 $aonline model selection 610 $aprecipitation nowcasting 610 $adeep learning 610 $aautoencoders 610 $aradar data 610 $ageneralization error 610 $arecurrent neural networks 610 $amachine learning 610 $amodel predictive control 610 $anonlinear systems 610 $aneural networks 610 $alow power 610 $aquantization 610 $aCNN architecture 610 $amulti-objective optimization 610 $agenetic algorithms 610 $aevolutionary computation 610 $aswarm intelligence 610 $aHeating, Ventilation and Air Conditioning (HVAC) 610 $ametaheuristics search 610 $abio-inspired algorithms 610 $asmart building 610 $asoft computing 610 $atraining 610 $aevolution of weights 610 $aartificial intelligence 610 $adeep neural networks 610 $aconvolutional neural network 610 $adeep compression 610 $aDNN 610 $aReLU 610 $afloating-point numbers 610 $ahardware acceleration 610 $aenergy dissipation 610 $aFLOW-3D 610 $ahydraulic jumps 610 $abed roughness 610 $asensitivity analysis 610 $afeature selection 610 $aevolutionary algorithms 610 $anature inspired algorithms 610 $ameta-heuristic optimization 610 $acomputational intelligence 615 7$aResearch & information: general 615 7$aMathematics & science 700 $aGabbay$b Freddy$4edt$01304465 702 $aGabbay$b Freddy$4oth 906 $aBOOK 912 $a9910557610303321 996 $aComputational Optimizations for Machine Learning$93027447 997 $aUNINA