LEADER 04870nam 2200505 450 001 996517755303316 005 20230729144051.0 010 $a3-031-25599-2 024 7 $a10.1007/978-3-031-25599-1 035 $a(MiAaPQ)EBC7211136 035 $a(Au-PeEL)EBL7211136 035 $a(CKB)26240745100041 035 $a(DE-He213)978-3-031-25599-1 035 $a(PPN)26909248X 035 $a(EXLCZ)9926240745100041 100 $a20230729d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aMachine learning, optimization, and data science $e8th international conference, LOD 2022, Certosa Di Pontignano, Italy, September 18-22, 2022, revised selected papers, Part I /$fGiuseppe Nicosia [and seven others], editors 205 $a1st ed. 2023. 210 1$aCham, Switzerland :$cSpringer Nature Switzerland AG,$d[2023] 210 4$dİ2023 215 $a1 online resource (639 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v13810 311 08$aPrint version: Nicosia, Giuseppe Machine Learning, Optimization, and Data Science Cham : Springer,c2023 9783031255984 320 $aIncludes bibliographical references and index. 327 $aExplainable Machine Learning for Drug Shortage Prediction in a Pandemic Setting -- Intelligent Robotic Process Automation for Supplier Document Management on E-Procurement Platforms -- Batch Bayesian Quadrature with Batch Updating Using Future Uncertainty Sampling -- Sensitivity analysis of Engineering Structures Utilizing Artificial Neural Networks and Polynomial -- Inferring Pathological Metabolic Patterns in Breast Cancer Tissue from Genome-Scale Models -- Deep Learning -- Machine Learning -- Reinforcement Learning -- Neural Networks -- Deep Reinforcement Learning -- Optimization -- Global Optimization -- Multi-Objective Optimization -- Computational Optimization -- Data Science -- Big Data -- Data Analytics -- Artificial Intelligence -- Detection of Morality in Tweets based on the Moral Foundation Theory -- Matrix completion for the prediction of yearly country and industry-level CO2 emissions -- A Benchmark for Real-Time Anomaly Detection Algorithms Applied in Industry 4.0 -- A Matrix Factorization-based Drug-virus Link Prediction Method for SARS CoV -- Drug Prioritization -- Hyperbolic Graph Codebooks -- A Kernel-Based Multilayer Perceptron Framework to Identify Pathways Related to Cancer Stages -- Loss Function with Memory for Trustworthiness Threshold Learning: Case of Face and Facial Expression Recognition -- Machine learning approaches for predicting Crystal Systems: a brief review and a case study -- LS-PON: a Prediction-based Local Search for Neural Architecture Search -- Local optimisation of Nystrm samples through stochastic gradient descent -- Explainable Machine Learning for Drug Shortage Prediction in a Pandemic Setting -- Intelligent Robotic Process Automation for Supplier Document Management on E-Procurement Platforms -- Batch Bayesian Quadrature with Batch Updating Using Future Uncertainty Sampling -- Sensitivity analysis of Engineering Structures Utilizing Artificial Neural Networks and Polynomial -- Inferring Pathological Metabolic Patterns in Breast Cancer Tissue from Genome-Scale Models -- Deep Learning -- Machine Learning -- Reinforcement Learning -- Neural Networks -- Deep Reinforcement Learning -- Optimization -- Global Optimization -- Multi-Objective Optimization -- Computational Optimization -- Data Science -- Big Data -- Data Analytics -- Artificial Intelligence. 330 $aThis two-volume set, LNCS 13810 and 13811, constitutes the refereed proceedings of the 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, together with the papers of the Second Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022. The total of 84 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 226 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v13810 606 $aMachine learning$vCongresses 606 $aMathematical optimization$vCongresses 615 0$aMachine learning 615 0$aMathematical optimization 676 $a060.68 702 $aNicosia$b Giuseppe 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996517755303316 996 $aMachine learning, optimization, and data science$91949690 997 $aUNISA