Author : Stefano Leonardi
Publisher :
Page : 798 pages
File Size : 20,23 MB
Release : 2013
Category : Computer science
ISBN : 9781450318693
Author : Kevin P. Murphy
Publisher : MIT Press
Page : 858 pages
File Size : 40,77 MB
Release : 2022-03-01
Category : Computers
ISBN : 0262369303
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Author : Amit Kumar
Publisher : Springer Nature
Page : 899 pages
File Size : 24,42 MB
Release : 2022-10-31
Category : Technology & Engineering
ISBN : 9811923507
This book presents original, peer-reviewed select articles from the International Conference on Cognitive & Intelligent Computing (ICCIC – 2021), held on December 11–12, 2021, at Hyderabad, India. The proceedings has cutting edge Research outcome related to Machine learning in control applications, Soft computing, Pattern Recognition, Decision Support Systems, Text analytics and NLP, Statistical Learning, Neural Network Learning, Learning Through Fuzzy Logic, Learning Through Evolution (Evolutionary Algorithms), Reinforcement Learning, Multi-Strategy Learning, Cooperative Learning, Planning And Learning, Multi-Agent Learning, Online And Incremental Learning, Scalability Of Learning Algorithms, Inductive Learning, Inductive Logic Programming, Bayesian Networks, Support Vector Machines, Case-Based Reasoning, Multi-Agent Systems, Human–Computer Interaction, Data Mining and Knowledge Discovery, Knowledge Management and Networks, Data Intensive Computing Architecture, Medicine, Health, Bioinformatics, and Systems Biology, Industrial and Engineering Applications, Security Applications, Smart Cities, Game Playing and Problem Solving, Intelligent Virtual Environments, Economics, Business, And Forecasting Applications. Articles in the book are carefully selected on the basis of their application orientation. The content is expected to be especially useful for Professionals, Researchers, Research students working in the area of cognitive and intelligent computing.
Author :
Publisher :
Page : 394 pages
File Size : 28,33 MB
Release : 2000
Category : Radio programs
ISBN :
Author : Sara Rodríguez González
Publisher : Springer Nature
Page : 229 pages
File Size : 34,35 MB
Release : 2021-09-09
Category : Technology & Engineering
ISBN : 3030868877
This book highlights the latest research on distributed computing and artificial intelligence. DCAI 2021 is a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing areas. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This year’s technical program will present both high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 55 papers were submitted to main track and special sessions, by authors from 24 different countries representing a truly “wide area network” of research activity. Moreover, DCAI 2021 Special Sessions have been a very useful tool in order to complement the regular program with new or emerging topics of particular interest to the participating community. The technical program of the Special Sessions of DCAI 2021 has selected 23 papers. We would like to thank all the contributing authors, the members of the Program Committees, the sponsors (IBM, Armundia Group, EurAI, AEPIA, APPIA, CINI, OIT, UGR, HU, SCU, USAL, AIR Institute and UNIVAQ) and the Organizing Committee of the University of Salamanca for their hard and highly valuable work.
Author : Diederik Aerts
Publisher : Springer Nature
Page : 178 pages
File Size : 33,42 MB
Release : 2019-09-09
Category : Science
ISBN : 3030259137
Recent years have been characterized by tremendous advances in quantum information and communication, both theoretically and experimentally. In addition, mathematical methods of quantum information and quantum probability have begun spreading to other areas of research, beyond physics. One exciting new possibility involves applying these methods to information science and computer science (without direct relation to the problems of creation of quantum computers). The aim of this Special Volume is to encourage scientists, especially the new generation (master and PhD students), working in computer science and related mathematical fields to explore novel possibilities based on the mathematical formalisms of quantum information and probability. The contributing authors, who hail from various countries, combine extensive quantum methods expertise with real-world experience in application of these methods to computer science. The problems considered chiefly concern quantum information-probability based modeling in the following areas: information foraging; interactive quantum information access; deep convolutional neural networks; decision making; quantum dynamics; open quantum systems; and theory of contextual probability. The book offers young scientists (students, PhD, postdocs) an essential introduction to applying the mathematical apparatus of quantum theory to computer science, information retrieval, and information processes.
Author : Mirjam Augstein
Publisher : Walter de Gruyter GmbH & Co KG
Page : 320 pages
File Size : 34,67 MB
Release : 2019-09-23
Category : Business & Economics
ISBN : 3110552485
Personalized and adaptive systems employ user models to adapt content, services, interaction or navigation to individual users’ needs. User models can be inferred from implicitly observed information, such as the user’s interaction history or current location, or from explicitly entered information, such as user profile data or ratings. Applications of personalization include item recommendation, location-based services, learning assistance and the tailored selection of interaction modalities. With the transition from desktop computers to mobile devices and ubiquitous environments, the need for adapting to changing contexts is even more important. However, this also poses new challenges concerning privacy issues, user control, transparency, and explainability. In addition, user experience and other human factors are becoming increasingly important. This book describes foundations of user modeling, discusses user interaction as a basis for adaptivity, and showcases several personalization approaches in a variety of domains, including music recommendation, tourism, and accessible user interfaces.
Author : Hakim Hacid
Publisher : Springer
Page : 527 pages
File Size : 10,21 MB
Release : 2018-10-20
Category : Computers
ISBN : 3030029255
The two-volume set LNCS 11233 and LNCS 11234 constitutes the proceedings of the 19th International Conference on Web Information Systems Engineering, WISE 2018, held in Dubai, United Arab Emirates, in November 2018. The 48 full papers and 21 short papers presented were carefully reviewed and selected from 209 submissions. The papers are organized in topical sections on blockchain, security, social network and security, social network, microblog data analysis, graph data, information extraction, text mining, recommender systems, medical data analysis, Web services and cloud computing, data stream and distributed computing, data mining techniques, entity linkage and semantics, Web applications, and data mining applications.
Author : Nada Lavrač
Publisher : Springer Nature
Page : 175 pages
File Size : 35,28 MB
Release : 2021-07-10
Category : Computers
ISBN : 3030688178
This monograph addresses advances in representation learning, a cutting-edge research area of machine learning. Representation learning refers to modern data transformation techniques that convert data of different modalities and complexity, including texts, graphs, and relations, into compact tabular representations, which effectively capture their semantic properties and relations. The monograph focuses on (i) propositionalization approaches, established in relational learning and inductive logic programming, and (ii) embedding approaches, which have gained popularity with recent advances in deep learning. The authors establish a unifying perspective on representation learning techniques developed in these various areas of modern data science, enabling the reader to understand the common underlying principles and to gain insight using selected examples and sample Python code. The monograph should be of interest to a wide audience, ranging from data scientists, machine learning researchers and students to developers, software engineers and industrial researchers interested in hands-on AI solutions.
Author : Patricia F. Zauchner
Publisher : Springer Nature
Page : 176 pages
File Size : 19,21 MB
Release :
Category :
ISBN : 3658450851
