Machine learning

In this book, innovative research using artificial neural networks (ANNs) is conducted to automate the sizing task of RF IC design, which is used in two different steps of the automatic design process.

This book provides a discussion of privacy in the following three parts: Privacy Issues in Data Aggregation; Privacy Issues in Indoor Localization; and Privacy-Preserving Offloading in MEC.

This book provides a comprehensive overview of Human Activity Detection or Recognition (HADR) systems.

The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022.

This book constitutes the proceedings of the 6th International Conference on Dynamics of Information Systems, DIS 2023, which took place in Prague, Czech Republic, in September 2023.

This book is the first work dedicated to the Bees Algorithm.

The SpringerBrief introduces FasTensor, a powerful parallel data programming model developed for big data applications.

This book constitutes the refereed post-conference proceedings of the Second EAI International Conference on AI for People, Democratizing AI, CAIP 2023, held in Bologna, Italy, during November 24-26, 2023.

This book constitutes the refereed post-conference proceedings of the 15th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2020, held in Shenzhen, China, in November 2020.

Welcome to your hands-on guide to artificial intelligence for IT operations (AIOps).

The seven-volume set LNCS 14850-14856 constitutes the proceedings of the 29th International Conference on Database Systems for Advanced Applications, DASFAA 2024, held in Gifu, Japan, in July 2024.

This book, at first, explores the evolution of the IoT to SIoT and offers a comprehensive understanding of SIoT and trust management vis-a-vis SIoT.

Reinforcement and Systemic Machine Learning for Decision Making There are always difficulties in making machines that learn from experience.

This Element provides theoretical and practical introductions to machine learning for social scientists in applying it to experimental data.

This Element analyses real-world trial courts data with state-of-the-art machine learning and causal inference methods.

This two-volume set LNCS 13344 and 13345 constitutes the proceedings of the 13th International Conference on Advances in Swarm Intelligence, ICSI 2022, which took place in Xi'an, China, in July 2022.

This book constitutes the refereed proceedings of the 23rd Conference on Medical Image Understanding and Analysis, MIUA 2019, held in Liverpool, UK, in July 2019.

This 13-volume set LNCS 14862-14874 constitutes - in conjunction with the 6-volume set LNAI 14875-14880 and the two-volume set LNBI 14881-14882 - the refereed proceedings of the 20th International Conference on Intelligent Computing, ICIC 2024, held in Tianjin, China, during August 5-8, 2024.

This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends, challenges, and applications.

The 8-volume set, comprising the LNCS books 13801 until 13809, constitutes the refereed proceedings of 38 out of the 60 workshops held at the 17th European Conference on Computer Vision, ECCV 2022.

This book introduces basic machine learning concepts and applications for a broad audience that includes students, faculty, and industry practitioners.

The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022.

Design, develop, and validate machine learning models with streaming data using the Scikit-Multiflow framework.

This comprehensive guide, featuring hand-picked examples of daily use cases, will walk you through the end-to-end predictive model-building cycle using the latest techniques and industry tricks.

A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

The advancement of biomedical engineering has enabled the generation of multi-omics data by developing high-throughput technologies, such as next-generation sequencing, mass spectrometry, and microarrays.

Learn and implement responsible AI models using Python.

This book presents an exploration of linkages among soil-water, agriculture, and climate change with a special focus on thematic areas for assessment, mitigation, and management of natural resources under climate change conditions.

Get to grips with building robust XGBoost models using Python and scikit-learn for deploymentKey FeaturesGet up and running with machine learning and understand how to boost models with XGBoost in no timeBuild real-world machine learning pipelines and fine-tune hyperparameters to achieve optimal resultsDiscover tips and tricks and gain innovative insights from XGBoost Kaggle winnersBook DescriptionXGBoost is an industry-proven, open-source software library that provides a gradient boosting framework for scaling billions of data points quickly and efficiently.

This volume constitutes selected papers presented during the Third International Conference on Intelligent Systems and Pattern Recognition, ISPR 2023, held in Hammamet, Tunisia, in May 2023.

This book gathers high-quality research papers presented at the International Conference on Computing in Engineering and Technology (ICCET 2020) [formerly ICCASP].

The multi-volume set of LNCS books with volume numbers 15301-15333 constitutes the refereed proceedings of the 27th International Conference on Pattern Recognition, ICPR 2024, held in Kolkata, India, during December 1-5, 2024.

Machine Learning, a vital and core area of artificial intelligence (AI), is propelling the AI field ever further and making it one of the most compelling areas of computer science research.

This book introduces the essentials of Python for the emerging fields of Machine Learning (ML) and Artificial Intelligence (AI).

This book presents recent advances in the field of scalable distributed computing including state-of-the-art research in the field of Cloud Computing, the Internet of Things (IoT), and Blockchain in distributed environments along with applications and findings in broad areas including Data Analytics, AI, and Machine Learning to address complex real-world problems.

The two-volume proceedings CCIS 1613 + 1614 constitute revised selected papers from the 6th International Conference on Advances in Computing and Data Sciences, ICACDS 2022, which was held in Kurnool, India in April 2022.

This book investigates in detail the deep learning (DL) techniques in electromagnetic (EM) near-field scattering problems, assessing its potential to replace traditional numerical solvers in real-time forecast scenarios.

The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29-October 4, 2024.

This book constitutes the refereed proceedings of the 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2023, which was held in conjunction with MICCAI 2023, in October 2023.

Your no-nonsense guide to making sense of machine learning Machine learning can be a mind-boggling concept for the masses, but those who are in the trenches of computer programming know just how invaluable it is.

This text presents a collection of mathematical exercises with the aim of guiding readers to study topics in statistical physics, equilibrium thermodynamics, information theory, and their various connections.

This book explores how to define, design, and maintain enterprise AI applications, exploring the impacts they will have on the teams who work with them.

Colorful example-rich introduction to the state-of-the-art for students in data science, as well as researchers and practitioners.

This book aims at updating the relevant computer science-related research communities, including professors, researchers, scientists, engineers and students, as well as the general reader from other disciplines, on the most recent advances in applications of methods based on Fusing Machine Learning Paradigms.

This book features best selected research papers presented at the International Conference on Machine Learning, Internet of Things, and Big Data (ICMIB 2021) held at Indira Gandhi Institute of Technology, Sarang, India, during December 2021.

This book constitutes the refereed proceedings of the 13th International Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2024, held as part of EvoStar 2024, in Aberystwyth, UK, April 3-5, 2024.

This two-volume set of LNCS 12463 and LNCS 12464 constitutes - in conjunction with the volume LNAI 12465 - the refereed proceedings of the 16th International Conference on Intelligent Computing, ICIC 2020, held in Bari, Italy, in October 2020.

Gain a working knowledge of prescriptive AI, its history, and its current and future trends.