Machine Learning: ECML 2000
Machine Learning: ECML 2000

Author: Ramon Lopez de Mantaras

Publisher: Springer

Published: 2007-03-06

Total Pages: 469

ISBN-13: 3540451641

DOWNLOAD EBOOK

The biennial European Conference on Machine Learning (ECML) series is intended to provide an international forum for the discussion of the latest high quality research results in machine learning and is the major European scienti?c event in the ?eld. The eleventh conference (ECML 2000) held in Barcelona, Catalonia, Spain from May 31 to June 2, 2000, has continued this tradition by attracting high quality papers from around the world. Scientists from 21 countries submitted 100 papers to ECML 2000, from which 20 were selected for long oral presentations and 23 for short oral presentations. This selection was based on the recommendations of at least two reviewers for each submitted paper. It is worth noticing that the number of papers reporting applications of machine learning has increased in comparison to past ECML conferences. We believe this fact shows the growing maturity of the ?eld. This volume contains the 43 accepted papers as well as the invited talks by Katharina Morik from the University of Dortmund and Pedro Domingos from the University of Washington at Seattle. In addition, three workshops were jointly organized by ECML 2000 and the European Network of Excellence - net: “Dealing with Structured Data in Machine Learning and Statistics W- stites”, “Machine Learning in the New Information Age” , and “Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Com- nation”.

Meta-Learning in Decision Tree Induction
Meta-Learning in Decision Tree Induction

Author: Krzysztof Grąbczewski

Publisher: Springer

Published: 2013-09-11

Total Pages: 349

ISBN-13: 3319009605

DOWNLOAD EBOOK

The book focuses on different variants of decision tree induction but also describes the meta-learning approach in general which is applicable to other types of machine learning algorithms. The book discusses different variants of decision tree induction and represents a useful source of information to readers wishing to review some of the techniques used in decision tree learning, as well as different ensemble methods that involve decision trees. It is shown that the knowledge of different components used within decision tree learning needs to be systematized to enable the system to generate and evaluate different variants of machine learning algorithms with the aim of identifying the top-most performers or potentially the best one. A unified view of decision tree learning enables to emulate different decision tree algorithms simply by setting certain parameters. As meta-learning requires running many different processes with the aim of obtaining performance results, a detailed description of the experimental methodology and evaluation framework is provided. Meta-learning is discussed in great detail in the second half of the book. The exposition starts by presenting a comprehensive review of many meta-learning approaches explored in the past described in literature, including for instance approaches that provide a ranking of algorithms. The approach described can be related to other work that exploits planning whose aim is to construct data mining workflows. The book stimulates interchange of ideas between different, albeit related, approaches.

Metalearning
Metalearning

Author: Pavel Brazdil

Publisher: Springer Nature

Published: 2022

Total Pages: 349

ISBN-13: 3030670244

DOWNLOAD EBOOK

This open access book as one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, automated machine learning (AutoML) is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary interventions from the user. This book offers a comprehensive and thorough introduction to almost all aspects of metalearning and AutoML, covering the basic concepts and architecture, evaluation, datasets, hyperparameter optimization, ensembles and workflows, and also how this knowledge can be used to select, combine, compose, adapt and configure both algorithms and models to yield faster and better solutions to data mining and data science problems. It can thus help developers to develop systems that can improve themselves through experience. This book is a substantial update of the first edition published in 2009. It includes 18 chapters, more than twice as much as the previous version. This enabled the authors to cover the most relevant topics in more depth and incorporate the overview of recent research in the respective area. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining, data science and artificial intelligence.

Discovery Science
Discovery Science

Author: Steffen Lange

Publisher: Springer

Published: 2003-08-03

Total Pages: 478

ISBN-13: 3540361820

DOWNLOAD EBOOK

This volume contains the papers presented at the 5th International Conference on Discovery Science (DS 2002) held at the Mövenpick Hotel, Lub ̈eck, G- many, November 24-26, 2002. The conference was supported by CorpoBase, DFKI GmbH, and JessenLenz. The conference was collocated with the 13th International Conference on - gorithmic Learning Theory (ALT 2002). Both conferences were held in parallel and shared?ve invited talks as well as all social events. The combination of ALT 2002 and DS 2002 allowed for a comprehensive treatment of recent de- lopments in computational learning theory and machine learning - some of the cornerstones of discovery science. In response to the call for papers 76 submissions were received. The program committee selected 17 submissions as regular papers and 29 submissions as poster presentations of which 27 have been submitted for publication. This selection was based on clarity, signi?cance, and originality, as well as on relevance to the rapidly evolving?eld of discovery science.

Genetic and Evolutionary Computation--GECCO 2003
Genetic and Evolutionary Computation--GECCO 2003

Author: Erick Cantú-Paz

Publisher: Springer Science & Business Media

Published: 2003-07-08

Total Pages: 1294

ISBN-13: 3540406026

DOWNLOAD EBOOK

The set LNCS 2723 and LNCS 2724 constitutes the refereed proceedings of the Genetic and Evolutionaty Computation Conference, GECCO 2003, held in Chicago, IL, USA in July 2003. The 193 revised full papers and 93 poster papers presented were carefully reviewed and selected from a total of 417 submissions. The papers are organized in topical sections on a-life adaptive behavior, agents, and ant colony optimization; artificial immune systems; coevolution; DNA, molecular, and quantum computing; evolvable hardware; evolutionary robotics; evolution strategies and evolutionary programming; evolutionary sheduling routing; genetic algorithms; genetic programming; learning classifier systems; real-world applications; and search based softare engineering.

Planning Based on Decision Theory
Planning Based on Decision Theory

Author: Giacomo Della Riccia

Publisher: Springer

Published: 2014-05-04

Total Pages: 170

ISBN-13: 3709125308

DOWNLOAD EBOOK

Planning of actions based on decision theory is a hot topic for many disciplines. Seemingly unlimited computing power, networking, integration and collaboration have meanwhile attracted the attention of fields like Machine Learning, Operations Research, Management Science and Computer Science. Software agents of e-commerce, mediators of Information Retrieval Systems and Database based Information Systems are typical new application areas. Until now, planning methods were successfully applied in production, logistics, marketing, finance, management, and used in robots, software agents etc. It is the special feature of the book that planning is embedded into decision theory, and this will give the interested reader new perspectives to follow-up.

Knowledge Discovery in Databases: PKDD 2004
Knowledge Discovery in Databases: PKDD 2004

Author: Jean-Francois Boulicaut

Publisher: Springer Science & Business Media

Published: 2004-09-10

Total Pages: 578

ISBN-13: 3540231080

DOWNLOAD EBOOK

This book constitutes the refereed proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2004, held in Pisa, Italy, in September 2004 jointly with ECML 2004. The 39 revised full papers and 9 revised short papers presented together with abstracts of 5 invited talks were carefully reviewed and selected from 194 papers submitted to PKDD and 107 papers submitted to both, PKDD and ECML. The papers present a wealth of new results in knowledge discovery in databases and address all current issues in the area.

Case-Based Reasoning Research and Development
Case-Based Reasoning Research and Development

Author: David W. Aha

Publisher: Springer

Published: 2003-05-15

Total Pages: 769

ISBN-13: 3540445935

DOWNLOAD EBOOK

The 2001 International Conference on Case-Based Reasoning (ICCBR 2001, www.iccbr.org/iccbr01), the fourth in the biennial ICCBR series (1995 in Sesimbra, Portugal; 1997 in Providence, Rhode Island (USA); 1999 in Seeon, Germany), was held during 30 July – 2 August 2001 in Vancouver, Canada. ICCBR is the premier international forum for researchers and practitioners of case based reasoning (CBR). The objectives of this meeting were to nurture significant, relevant advances made in this field (both in research and application), communicate them among all attendees, inspire future advances, and continue to support the vision that CBR is a valuable process in many research disciplines, both computational and otherwise. ICCBR 2001 was the first ICCBR meeting held on the Pacific coast, and we used the setting of beautiful Vancouver as an opportunity to enhance participation from the Pacific Rim communities, which contributed 28% of the submissions. During this meeting, we were fortunate to host invited talks by Ralph Bergmann, Ken Forbus, Jaiwei Han, Ramon López de Mántaras, and Manuela Veloso. Their contributions ensured a stimulating meeting; we thank them all.

Innovations in Applied Artificial Intelligence
Innovations in Applied Artificial Intelligence

Author: Bob Orchard

Publisher: Springer

Published: 2004-04-22

Total Pages: 1293

ISBN-13: 3540246770

DOWNLOAD EBOOK

“Intelligent systems must perform in order to be in demand. ” Intelligent systems technology is being applied steadily in solving many day-to-day problems. Each year the list of real-world deployed applications that inconspicuously host the results of research in the area grows considerably. These applications are having a significant impact in industrial operations, in financial circles, in transportation, in education, in medicine, in consumer products, in games and elsewhere. A set of selected papers presented at the seventeenth in the series of conferences on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2004), sponsored by the International Society of Applied Intelligence, is offered in this manuscript. These papers highlight novel applications of the technology and show how new research could lead to new and innovative applications. We hope that you find these papers to be educational, useful in your own research, and stimulating. In addition, we have introduced some special sessions to emphasize a few areas of artificial intelligence (AI) that are either relatively new, have received considerable attention recently or perhaps have not yet been represented well. To this end, we have included special sessions on e-learning, bioinformatics, and human-robot interaction (HRI) to complement the usual offerings in areas such as data mining, machine learning, intelligent systems, neural networks, genetic algorithms, autonomous agents, natural language processing, intelligent user interfaces, evolutionary computing, fuzzy logic, computer vision and image processing, reasoning, heuristic search, security, Internet applications, constraint satisfaction problems, design, and expert systems.