Machine learning

The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns.

Markov Decision Processes (MDPs) are widely popular in Artificial Intelligence for modeling sequential decision-making scenarios with probabilistic dynamics.

Cooperative game theory is a branch of (micro-)economics that studies the behavior of self-interested agents in strategic settings where binding agreements among agents are possible.

Computational social choice is an expanding field that merges classical topics like economics and voting theory with more modern topics like artificial intelligence, multiagent systems, and computational complexity.

Human computation is a new and evolving research area that centers around harnessing human intelligence to solve computational problems that are beyond the scope of existing Artificial Intelligence (AI) algorithms.

Automated trading in electronic markets is one of the most common and consequential applications of autonomous software agents.

The visual recognition problem is central to computer vision research.

One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery.

Support Vectors Machines have become a well established tool within machine learning.

Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective.

Data integration is a critical problem in our increasingly interconnected but inevitably heterogeneous world.

Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this is key to their success (e.

Semi-supervised learning is a learning paradigm concerned with the study of how computers and natural systems such as humans learn in the presence of both labeled and unlabeled data.

Artificial systems that think and behave intelligently are one of the most exciting and challenging goals of Artificial Intelligence.

Game theory is the mathematical study of interaction among independent, self-interested agents.

Robotics technology has recently advanced to the point of being widely accessible for relatively low-budget research, as well as for graduate, undergraduate, and even secondary and primary school education.

Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning.

Representations are at the heart of artificial intelligence (AI).

The three-volume set LNCS 13245, 13246 and 13247 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held online, in April 2021.

This book covers recent trends and applications of nonlinear dynamics in various branches of society, science, and engineering.

This book provides a comprehensive introduction to processing-in-memory (PIM) technology, from its architectures to circuits implementations on multiple memory types and describes how it can be a viable computer architecture in the era of AI and big data.

This book constitutes the Second International Challenge on Kidney and Kidney Tumor Segmentation, KiTS 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021.

This textbook provides an in-depth exploration of statistical learning with reproducing kernels, an active area of research that can shed light on trends associated with deep neural networks.

This book constitutes the Second 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021.

This two-volume set LNCS 13185 and 13186 constitutes the refereed proceedings of the 44th European Conference on IR Research, ECIR 2022, held in April 2022, due to the COVID-19 pandemic.

This book covers the medical condition of diabetic patients, their early symptoms and methods conventionally used for diagnosing and monitoring diabetes.

This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems.

This book presents new technologies and applications in deep learning, artificial intelligence and robotics.

This book is a timely book to summarize the latest developments in the optimization of tuned mass dampers covering all classical approaches and new trends including metaheuristic algorithms.

This book takes the notions of adaptivity and learning from the realm of engineering into the realm of biology and natural processes.

This book presents recent improvements in peridynamic modeling of structures.

This book offers a comprehensive review of collision avoidance techniques and safe trajectory planning for manned and unmanned ships, together with extensive information on how to develop and implement algorithms for applications in real-world settings.

This book explores new and novel applications of machine learning, deep learning, and artificial intelligence that are related to major challenges in the field of cybersecurity.

Federated Learning: A Comprehensive Overview of Methods and Applications presents an in-depth discussion of the most important issues and approaches to federated learning for researchers and practitioners.

This volume constitutes selected papers presented at the 28th International Conference on Systems, Signals and Image Processing, IWSSIP 2021, held in Bratislava, Slovakia, in June 2021.

This book constitutes three challenges that were held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, which was planned to take place in Strasbourg, France but changed to an online event due to the COVID-19 pandemic.

This book aims to present dominant applications and use cases of the fast-evolving DT and determines vital Industry 4.

This textbook introduces readers to the theoretical aspects of machine learning (ML) algorithms, starting from simple neuron basics, through complex neural networks, including generative adversarial neural networks and graph convolution networks.

This book focuses on research and development aspects of building data analytics workflows that address various challenges of e-learning applications.

This book provides a systematic and comprehensive overview of AI and machine learning which have got the ability to identify patterns in large and complex data sets.

This second edition textbook covers a coherently organized framework for text analytics, which integrates material drawn from the intersecting topics of information retrieval, machine learning, and natural language processing.

This book constitutes the proceedings of the 9th International Conference on Big Data Analytics, BDA 2021, which took place virtually during December 7-9, 2021.

There are several popular books published in Healthcare Computational Informatics like Computational Bioengineering and Bioinformatics (2020), Springer; Health Informatics (2017), Springer; Health Informatics Vision: From Data via Information to Knowledge (2019), IOS Press; Data Analytics in Biomedical Engineering and Healthcare (2020), Elsevier.

Covid-19 has shown us the importance of mathematical and statistical models to interpret reality, provide forecasts, and explore future scenarios.

This SpringerBrief presents novel methods of approaching challenging problems in the reconstruction of accurate 3D models and serves as an introduction for further 3D reconstruction methods.

This book constitutes selected and revised papers from the Second Silicon Valley Cybersecurity Conference, held in San Jose, USA, in December 2021.

The three volume set LNCS 13155, 13156, and 13157 constitutes the refereed proceedings of the 21st International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2021, which was held online during December 3-5, 2021.

This book constitutes the Second Diabetic Foot Ulcers Grand Challenge, DFUC 2021, which was held on September 27, 2021, in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021.

This book includes the proceedings of the third workshop on recommender systems in fashion and retail (2021), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field.

This book constitutes the proceedings of the 12th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2021, as well as the M&Ms-2 Challenge: Multi-Disease, Multi-View and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge.