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Computational Learning Theory
  • Language: en
  • Pages: 412

Computational Learning Theory

This book is tailored for students and professionals as well as novices from other fields to mass spectrometry. It will guide them from the basics to the successful application of mass spectrometry in their daily research. Starting from the very principles of gas-phase ion chemistry and isotopic properties, it leads through the design of mass analyzers and ionization methods in use to mass spectral interpretation and coupling techniques. Step by step the readers will learn how mass spectrometry works and what it can do as a powerful tool in their hands. The book comprises a balanced mixture of practice-oriented information and theoretical background. The clear layout, a wealth of high-quality figures and a database of exercises and solutions, accessible via the publisher's web site, support teaching and learning.

Computational Learning Theory
  • Language: en
  • Pages: 639

Computational Learning Theory

This book constitutes the refereed proceedings of the 14th Annual and 5th European Conferences on Computational Learning Theory, COLT/EuroCOLT 2001, held in Amsterdam, The Netherlands, in July 2001. The 40 revised full papers presented together with one invited paper were carefully reviewed and selected from a total of 69 submissions. All current aspects of computational learning and its applications in a variety of fields are addressed.

Advanced Lectures on Machine Learning
  • Language: en
  • Pages: 267

Advanced Lectures on Machine Learning

  • Type: Book
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  • Published: 2003-07-01
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  • Publisher: Springer

Machine Learning has become a key enabling technology for many engineering applications and theoretical problems alike. To further discussions and to dis- minate new results, a Summer School was held on February 11–22, 2002 at the Australian National University. The current book contains a collection of the main talks held during those two weeks in February, presented as tutorial chapters on topics such as Boosting, Data Mining, Kernel Methods, Logic, Reinforcement Learning, and Statistical Learning Theory. The papers provide an in-depth overview of these exciting new areas, contain a large set of references, and thereby provide the interested reader with further information to start or to...

Learning Theory
  • Language: en
  • Pages: 703

Learning Theory

  • Type: Book
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  • Published: 2005-06-28
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  • Publisher: Springer

This volume contains papers presented at the Eighteenth Annual Conference on Learning Theory (previously known as the Conference on Computational Learning Theory) held in Bertinoro, Italy from June 27 to 30, 2005. The technical program contained 45 papers selected from 120 submissions, 3 open problems selected from among 5 contributed, and 2 invited lectures. The invited lectures were given by Sergiu Hart on “Uncoupled Dynamics and Nash Equilibrium”, and by Satinder Singh on “Rethinking State, Action, and Reward in Reinforcement Learning”. These papers were not included in this volume. The Mark Fulk Award is presented annually for the best paper co-authored by a student. The student ...

Learning Theory
  • Language: en
  • Pages: 657

Learning Theory

This book constitutes the refereed proceedings of the 17th Annual Conference on Learning Theory, COLT 2004, held in Banff, Canada in July 2004. The 46 revised full papers presented were carefully reviewed and selected from a total of 113 submissions. The papers are organized in topical sections on economics and game theory, online learning, inductive inference, probabilistic models, Boolean function learning, empirical processes, MDL, generalisation, clustering and distributed learning, boosting, kernels and probabilities, kernels and kernel matrices, and open problems.

Discovery Science
  • Language: en
  • Pages: 500

Discovery Science

  • Type: Book
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  • Published: 2016-10-12
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  • Publisher: Springer

This book constitutes the proceedings of the 17th International Conference on Discovery Science, DS 2016, held in banff, AB, Canada in October 2015. The 30 full papers presented together with 5 abstracts of invited talks in this volume were carefully reviewed and selected from 60 submissions.The conference focuses on following topics: Advances in the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, and intelligent data analysis, as well as their application in various scientific domains.

Learning Theory and Kernel Machines
  • Language: en
  • Pages: 761

Learning Theory and Kernel Machines

This book constitutes the joint refereed proceedings of the 16th Annual Conference on Computational Learning Theory, COLT 2003, and the 7th Kernel Workshop, Kernel 2003, held in Washington, DC in August 2003. The 47 revised full papers presented together with 5 invited contributions and 8 open problem statements were carefully reviewed and selected from 92 submissions. The papers are organized in topical sections on kernel machines, statistical learning theory, online learning, other approaches, and inductive inference learning.

Inductive Logic Programming
  • Language: en
  • Pages: 437

Inductive Logic Programming

This book constitutes the refereed proceedings of the 15th International Conference on Inductive Logic Programming, ILP 2005, held in Bonn, Germany, in August 2005. The 24 revised full papers presented together with the abstract of 4 invited lectures were carefully reviewed and selected for inclusion in the book. The papers address all current topics in inductive logic programming, ranging from theoretical and methodological issues to advanced applications in various areas, also including more diverse forms of non-propositional learning.

Concentration Inequalities
  • Language: en
  • Pages: 492

Concentration Inequalities

Describes the interplay between the probabilistic structure (independence) and a variety of tools ranging from functional inequalities to transportation arguments to information theory. Applications to the study of empirical processes, random projections, random matrix theory, and threshold phenomena are also presented.

Geometric Aspects of Functional Analysis
  • Language: en
  • Pages: 299

Geometric Aspects of Functional Analysis

  • Type: Book
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  • Published: 2004-08-30
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  • Publisher: Springer

The Israeli GAFA seminar (on Geometric Aspect of Functional Analysis) during the years 2002-2003 follows the long tradition of the previous volumes. It reflects the general trends of the theory. Most of the papers deal with different aspects of the Asymptotic Geometric Analysis. In addition the volume contains papers on related aspects of Probability, classical Convexity and also Partial Differential Equations and Banach Algebras. There are also two expository papers on topics which proved to be very much related to the main topic of the seminar. One is Statistical Learning Theory and the other is Models of Statistical Physics. All the papers of this collection are original research papers.