Machine Learning, Optimization, and Data Science

Machine Learning, Optimization, and Data Science

8th International Conference, LOD 2022, Certosa di Pontignano, Italy, September 18-22, 2022, Revised Selected Papers, Part I

Nicosia, Giuseppe; Pardalos, Panos; La Malfa, Gabriele; Umeton, Renato; Giuffrida, Giovanni; Di Fatta, Giuseppe; Ojha, Varun; La Malfa, Emanuele

Springer International Publishing AG

03/2023

616

Mole

Inglês

9783031255984

15 a 20 dias

Descrição não disponível.
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.- 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.
adaptive control systems;anomaly detection;artificial intelligence;automation;bayesian networks;big data;computer crime;computer security;damage detection;data mining;database systems;deep learning;engineering structures;evolutionary algorithms;facial expression recognition;fuzzy control;fuzzy sets;image processing;machine learning