Display options:

    machine learning

    part of the Copac national, academic & specialist library catalogue.

    1. Search result: 1.

      Cover image

      Title

      Machine Learning and Cybernetics (ICMLC), 2011 International Conference on

      Series
      • Online access with subscription: IEEE IET Electronic Library. Conferences.
      Published
      • Piscataway : Institute of Electrical and Electronics Engineers 2011
      ISBN
      • 9781457703058
      ISSN
      • 2160-133X
      Notes
      • Publication number: 6009138.
      • IEEE subject headings: Aerospace / Bioengineering / Communication, Networking & Broadcasting / Components, Circuits, Devices & Systems / Computing & Processing (Hardware/Software) / Signal Processing & Analysis.
      • Reproduction available: Electronic resource. Piscataway : Institute of Electrical and Electronics Engineers, 2011.
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Machine%20Learning%20and%20Cybernetics%20(ICMLC)%2C%202011%20International
      Format
      • Online

      Held At:

      1. Liverpool University Online
    2. Search result: 2.

      Title

      2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA)

      Series
      • Online access: IEEE (Institute of Electrical and Electronics Engineers) IEEE/IET Electronic Library (IEL)
      Published
      • IEEE / Institute of Electrical and Electronics Engineers Incorporated.
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=2015%20IEEE%2014th%20International%20Conference%20on%20Machine
      Format
      • Online

      Held At:

      1. Liverpool University Online
    3. Search result: 3.

      Cover image

      Title

      Case-based learning / edited by Janet L. Kolodner.

      Other titles
      • Machine learning.
      Published
      • Boston ; London : Kluwer Academic Publishers c1993
      Physical description
      363p : ill. ; 25 cm.
      ISBN
      • 0792393430
      • 9780792393436
      Notes
      • "Reprinted from: Machine learning. Vol.10, no.3 (1993)".
      • Includes bibliographical references and index.
      Summary
      • Case-based reasoning means reasoning based on remembering previous experiences. A reasoner using old experiences (cases) might use those cases to suggest solutions to problems, to point out potential problems with a solution being computed, to interpret a new situation and make predictions about what might happen, or to create arguments justifying some conclusion. A case-based reasoner solves new problems by remembering old situations and adapting their solutions. It interprets new situations by remembering old similar situations and comparing and contrasting the new one to old ones to see where it fits best. Case-based reasoning combines reasoning with learning. It spans the whole reasoning cycle. A situation is experienced. Old situations are used to understand it. Old situations are used to solve a problem (if there is one to be solved). Then the new situation is inserted into memory alongside the cases it used for reasoning, to be used another time. The key to this reasoning method, then, is remembering. Remembering has two parts: integrating cases or experiences into memory when they happen and recalling them in appropriate situations later on. The case-based reasoning community calls this related set of issues the indexing problem. In broad terms, it means finding in memory the experience closest to a new situation. In narrower terms, it can be described as a two-part problem: * assigning indexes or labels to experiences when they are put into memory that describe the situations to which they are applicable, so that they can be recalled later; and * at recall time, elaborating the new situation in enough detail so that the indexes it would have if it were in the memory are identified. Case-Based Learning is an edited volume of original research comprising invited contributions by leading workers. This work has also been published as a special issues of MACHINE LEARNING, Volume 10, No. 3.
      Other names
      • Kolodner, Janet L.
      Genre
      • Illustrated
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Case-based%20learning
      Format
      • Printed

      This is a merged record. View the constituent records by format:

      3.1

      Title

      Case-based learning / edited by Janet L. Kolodner.

      Other titles
      • Machine learning.
      Published
      • Boston ; London : Kluwer Academic Publishers c1993
      Physical description
      363p : ill. ; 25 cm.
      ISBN
      • 0792393430
      Notes
      • "Reprinted from: Machine learning. Vol.10, no.3 (1993)".
      • Includes bibliographical references and index.
      Other names
      • Kolodner, Janet L.
      Genre
      • Illustrated
      Format
      • Printed

      Held At:

      1. Birmingham University Printed

      3.2

      Title

      Case-based learning / edited by Janet L. Kolodner.

      Published
      • Boston ; London : Kluwer Academic Publishers c1993
      Physical description
      363p. : ill. ; 25cm.
      ISBN
      • 0792393430
      Notes
      • Includes bibliographical references and index.
      Other names
      • Kolodner, Janet L.
      Genre
      • Illustrated
      Format
      • Printed

      Held At:

      1. British Library Printed

      3.3

      Title

      Case-based learning / edited by Janet L. Kolodner.

      Published
      • Boston ; London : Kluwer Academic Publishers c1993
      Physical description
      363p : ill. ; 25 cm.
      ISBN
      • 0792393430
      • 9780792393436
      Notes
      • "Reprinted from: Machine learning. Vol.10, no.3 (1993)".
      • Includes bibliographical references and index.
      Other names
      • Kolodner, Janet L.
      Genre
      • Illustrated
      Format
      • Printed

      Held At:

      1. Manchester University Printed
    4. Search result: 4.

      Title

      2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA)

      Series
      • Online access: IEEE (Institute of Electrical and Electronics Engineers) IEEE/IET Electronic Library (IEL)
      Published
      • IEEE / Institute of Electrical and Electronics Engineers Incorporated.
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=2015%20IEEE%2014th%20International%20Conference%20on%20Machine
      Format
      • Online

      Held At:

      1. Liverpool University Online
    5. Search result: 5.

      Cover image

      Title

      Machine learning : an integrated framework and its applications / F. Bergadano and A. Giordana, L. Saitta.

      Author
      • Bergadano, F. (Francesco)
      Series
      • Ellis Horwood series in artificial intelligence
      • Ellis Horwood series in artificial intelligence.
      Published
      • New York ; London : Ellis Horwood 1991
      Physical description
      146p. : ill. ; 24cm.
      ISBN
      • 013541749X
      Notes
      • Includes index.
      • Bibliography: p130-144p.
      Other names
      • Giordana, A. (Attilio)
      • Saitta, Lorenza 1944-
      Genre
      • Illustrated
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Machine%20learningan%20integrated%20framework%20and%20its%20applications
      Format
      • Printed

      This is a merged record. View the constituent records by format:

      5.1

      Title

      Machine learning : an integrated framework and its applications. / [By Bergadano, F.]

      Author
      • Bergadano, F.
      Series
      • Ellis Horwood series in artificial intelligence
      • Ellis Horwood series in artificial intelligence
      Published
      • New York : Ellis Horwood 1991
      Physical description
      p. ; cm.
      ISBN
      • 013541749X
      Other names
      • Giordana, A.
      • Saitta, Lorenza.
      Format
      • Printed

      Held At:

      1. Aberdeen University Printed

      5.2

      Title

      Machine learning : an integrated framework and its applications / F. Bergadano and A. Giordana, L. Saitta.

      Author
      • Bergadano, F. (Francesco)
      Series
      • Ellis Horwood series in artificial intelligence
      Published
      • New York ; London : Ellis Horwood 1991
      Physical description
      146p : ill. ; 24 cm.
      ISBN
      • 013541749X
      Other names
      • Giordana, A. (Attilio)
      • Saitta, Lorenza 1944-
      Genre
      • Illustrated
      Format
      • Printed

      Held At:

      1. Birmingham University Printed

      5.3

      Title

      Machine learning : an integrated framework and its applications / F. Bergadano and A. Giordana, L. Saitta.

      Author
      • Bergadano, F. (Francesco)
      Series
      • Ellis Horwood series in artificial intelligence
      Published
      • New York ; London : Ellis Horwood 1991
      Physical description
      146p. : ill. ; 24cm.
      ISBN
      • 013541749X
      Notes
      • Bibliography: p130-144p.-Includes index.
      Other names
      • Giordana, A. (Attilio)
      • Saitta, Lorenza 1944-
      Genre
      • Illustrated
      Format
      • Printed

      Held At:

      1. British Library Printed

      5.4

      Title

      Machine learning : an integrated framework and its applications. / [By Bergando, F.]

      Author
      • Bergando, F.
      Series
      • Ellis Horwood series in artificial intelligence
      Published
      • Ellis Horwood 1991
      ISBN
      • 013541749X
      Other names
      • Giordana, A.
      • Saitta, L.
      Format
      • Printed

      Held At:

      1. British Library Printed

      5.5

      Title

      Machine learning : an integrated framework and its applications / F. Bergadano and A. Giordana, L. Saitta.

      Author
      • Bergadano, Francesco 1963-
      Series
      • Ellis Horwood series in artificial intelligence
      Published
      • New York : Ellis Horwood 1991
      Physical description
      vi,146p ; 24cm.
      ISBN
      • 013541749X
      Notes
      • Text on end-papers.
      Other names
      • Giordana, A. (Attilio)
      • Saitta, Lorenza 1944-
      Format
      • Printed

      Held At:

      1. Cambridge University Printed

      5.6

      Title

      Machine learning : an integrated framework and its applictions / F. Bergadano and A. Giordana and L. Saitta.

      Author
      • Bergadano, F. (Francesco)
      Series
      • Ellis Horwood series in artificial intelligence
      • Ellis Horwood series in artificial intelligence
      Published
      • New York ; London : Ellis Horwood 1991
      ISBN
      • 013541749X
      Other names
      • Giordana, A. (Attilio)
      • Saitta, L. (Lorenza)
      Format
      • Printed

      5.7

      Title

      Machine learning : an integrated framework and its applications / F. Bergadano and A. Giordana, L. Saitta.

      Author
      • Bergadano, F. (Francesco)
      Series
      • Ellis Horwood series in artificial intelligence
      Published
      • New York ; London : Ellis Horwood 1991
      Physical description
      146p : ill ; 24cm.
      ISBN
      • 013541749X
      Notes
      • Bibliography: p130-144p.-Includes index.
      Other names
      • Giordana, A. (Attilio)
      • Saitta, Lorenza 1944-
      Genre
      • Illustrated
      Format
      • Printed

      Held At:

      1. National Library of Wales Printed

      5.8

      Title

      Machine learning : an integrated framework and its applications / F. Bergadano and A. Giordana, L. Saitta.

      Author
      • Bergadano, Francesco 1963-
      Series
      • Ellis Horwood series in artificial intelligence.
      Published
      • New York ; London : Ellis Horwood 1991
      Physical description
      vi, 146 p. : ill ; 24 cm.
      ISBN
      • 013541749X
      Notes
      • Text on end-papers.
      • Bibliography: p130-144p.-Includes index.
      Other names
      • Giordana, A. (Attilio)
      • Saitta, Lorenza 1944-
      Genre
      • Illustrated
      Format
      • Printed

      Held At:

      1. Oxford University Printed

      5.9

      Title

      Machine learning : an integrated framework and its applications / F. Bergadano and A. Giordana, L. Saitta.

      Author
      • Bergadano, F. (Francesco)
      Series
      • Ellis Horwood series in artificial intelligence.
      Published
      • New York ; London : Ellis Horwood 1991
      Physical description
      146p : ill. ; 24 cm.
      ISBN
      • 013541749X
      Notes
      • Bibliography: p130-144p.-Includes index.
      Other names
      • Giordana, A. (Attilio)
      • Saitta, Lorenza 1944-
      Genre
      • Illustrated
      Format
      • Printed

      Held At:

      1. Queen's University Belfast Printed

      5.10

      Title

      Machine learning : an integrated framework and its applications / (by) F. Bergadano, A. Giordana and L. Saitta.

      Author
      • Bergadano, Francesco 1963-
      Published
      • New York : Ellis Horwood 1991
      ISBN
      • 013541749X
      • 9780135417492
      Other names
      • Giordana, A.
      • Saitta, L.
      Format
      • Printed

      Held At:

      1. Sussex University Printed

      5.11

      Title

      Machine learning : an integrated framework and its applications / F. Bergadano and A. Giordana, L. Saitta.

      Author
      • Bergadano, F. (Francesco)
      Series
      • Ellis Horwood series in artificial intelligence
      Published
      • New York ; London : Ellis Horwood 1991
      Physical description
      146p. : ill. ; 24cm.
      ISBN
      • 013541749X
      Notes
      • Includes index.
      • Bibliography: p130-144p.
      Other names
      • Giordana, A. (Attilio)
      • Saitta, Lorenza 1944-
      Genre
      • Illustrated
      Format
      • Printed

      Held At:

      1. Trinity College Dublin Printed
    6. Search result: 6.

      Cover image

      Title

      Proceedings, Twentieth International Conference on Machine Learning / edited by Tom Fawcett and Nina Mishra.

      Author
      • International Conference on Machine Learning : (20th : 2003 : Washington, D.C.)
      Other titles
      • ICML 2003.
      Published
      • Menlo Park : AAAI Press c2003
      Physical description
      2 v.
      ISBN
      • 1577351894
      Notes
      • Conference held in Washington, D.C., from August 21-24, 2003. Related title - ICML 2003.
      Other names
      • Fawcett, Tom.
      • Mishra, Nina.
      • American Association for Artificial Intelligence.
      Genre
      • Conference publication
      • Illustrated
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Proceedings%2C%20Twentieth%20International%20Conference%20on
      Format
      • Printed

      This is a merged record. View the constituent records by format:

      6.1

      Title

      Proceedings, twentieth international conference on machine learning / edited by Tom Fawcett and Nina Mishra.

      Published
      • AAAI Press 2003
      Physical description
      2 v.
      ISBN
      • 1577351894 (pbk)
      Other names
      • Fawcett, Tom.
      • Mishra, Nina.
      Genre
      • Conference publication
      Format
      • Printed

      Held At:

      1. British Library Printed

      6.2

      Title

      Proceedings, Twentieth International Conference on Machine Learning / edited by Tom Fawcett and Nina Mishra.

      Author
      • International Conference on Machine Learning : (20th : 2003 : Washington, D.C.)
      Other titles
      • ICML 2003.
      Published
      • Menlo Park : AAAI Press c2003
      Physical description
      2 v.
      ISBN
      • 1577351894
      Notes
      • Conference held in Washington, D.C., from August 21-24, 2003. Related title - ICML 2003.
      Other names
      • Fawcett, Tom.
      • Mishra, Nina.
      • American Association for Artificial Intelligence.
      Genre
      • Conference publication
      • Illustrated
      Format
      • Printed

      Held At:

      1. Bristol University Printed

      Held At:

      1. Bristol University Printed
      2. British Library Printed
    7. Search result: 7.

      Cover image

      Title

      Dictionaries and language learning : how can dictionaries help human & machine learning? : papers submitted to the Third ASIALEX Biennial International Conference, Meikai University, Urayasu, Chiba, Japan, August 27-29, 2003 / edited by Minoru Murata, Shigeru Yamada and Yukio Tono.

      Author
      • Yazhou ci shu xue hui. Conference 2003 : Toyko, Japan)
      Published
      • Chiba, Japan : Asian Association for Lexicography 2003
      Physical description
      vi, 499 p. : charts. ; 30 cm.
      ISBN
      • 499017710X
      Notes
      • At head of title: Asialex '03 Toyko Proceedings.
      Audience
      • adult
      Other names
      • Murata, Minoru.
      • Tono, Yukio.
      • Yamada, Shigeru.
      Genre
      • Conference publication
      • Illustrated
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Dictionaries%20and%20language%20learninghow%20can%20dictionaries
      Format
      • Printed

      Held At:

      1. Birmingham University Printed
    8. Search result: 8.

      Title

      Insider attack detection with machine learning techniques / Xiaotian Zhou.

      Author
      • Zhou, Xiaotian [author]
      Published
      2015
      Physical description
      50 pages : illustrations ; 30 cm.
      Notes
      • Supervisor: Dr Ioannis Agrafiotis, Dr Jassim Happa.
      • M.Sc. University of Oxford, 2015, Department of Computer Science, Oriel College.
      • Includes bibliographical references.
      Other names
      • University of Oxford [degree granting institution]
      Genre
      • Bibliography
      • Illustrated
      • text
      • Thesis
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Insider%20attack%20detection%20with%20machine%20learning%20techniques
      Format
      • Manuscript

      Held At:

      1. Oxford University Manuscript
    9. Search result: 9.

      Title

      A New Machine-Learning Technique Applied to the Game of Checkers / (by) A. K. Griffith.

      Author
      • Griffith, A. K.
      Series
      • Massachusetts Institute of Technology. Project Mac. Artificial Intelligence Laboratory. Artificial Intelligence Memoranda ; 94
      Published
      • M.I.T. 1966
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=New%20Machine-Learning%20Technique%20Applied%20to%20the%20Game
      Format
      • Printed

      Held At:

      1. Sussex University Printed
    10. Search result: 10.

      Cover image

      Title

      Machine learning - ECML '94 : European Conference on Machine Learning, Catania, Italy, April 6-8, 1994, proceedings / Francesco Bergadano, Luc De Raedt (eds.)

      Author
      • European Conference on Machine Learning (7th : 1994 : Catania, Italy)
      Series
      • Lecture notes in computer science ; 784. Lecture notes in artificial intelligence
      • Lecture notes in computer science ; 784.
      Other titles
      • Spine title: ECML-94.
      • ECML-94.
      Published
      • Berlin ; New York ; London : Springer c1994
      Physical description
      xi, 438 p.
      ISBN
      • 0387578684
      • 3540578684 (pbk.)
      Summary
      • This volume contains the proceedings of the European Conference on Machine Learning 1994, which continues the tradition of earlier meetings and which is a major forum for the presentation of the latest and most significant results in machine learning. Machine learning is one of the most important subfields of artificial intelligence and computer science, as it is concerned with the automation of learning processes. This volume contains two invited papers, 19 regular papers, and 25 short papers carefully reviewed and selected from in total 88 submissions. The papers describe techniques, algorithms, implementations, and experiments in the area of machine learning.
      Other names
      • Bergadano, Francesco.
      • De Raedt, Luc.
      Genre
      • Conference publication
      • Illustrated
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Machine%20learning%20-%20ECML%20'94European%20Conference%20on%20Machine
      Format
      • Printed

      Held At:

      1. Bristol University Printed
    11. Search result: 11.

      Cover image

      Title

      Machine learning - ECML '93 : European Conference on Machine Learning, Vienna, Austria, April 5-7 1993 : proceedings / Pavel B. Brazdil (ed.)

      Author
      • European Conference on Machine Learning (6th : 1993 : Vienna, Austria)
      Series
      • Lecture notes in computer science ; 667. Lecture notes in artificial intelligence
      • Lecture notes in computer science ; 667.
      Other titles
      • Spine title: ECML-93.
      • ECML-93.
      Published
      • Berlin ; New York ; London : Springer c1993
      Physical description
      xii, 469 p.
      ISBN
      • 0387566023
      • 3540566023 (pbk.)
      Summary
      • This volume contains the proceedings of the Eurpoean Conference on Machine Learning (ECML-93), continuing the tradition of the five earlier EWSLs (European Working Sessions on Learning). The aim of these conferences is to provide a platform for presenting the latest results in the area of machine learning. The ECML-93 programme included invited talks, selected papers, and the presentation of ongoing work in poster sessions. The programme was completed by several workshops on specific topics. The volume contains papers related to all these activities. The first chapter of the proceedings contains two invited papers, one by Ross Quinlan and one by Stephen Muggleton on inductive logic programming. The second chapter contains 18 scientific papers accepted for the main sessions of the conference. The third chapter contains 18 shorter position papers. The final chapter includes three overview papers related to the ECML-93 workshops.
      Other names
      • Brazdil, Pavel B.
      Genre
      • Conference publication
      • Illustrated
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Machine%20learning%20-%20ECML%20'93European%20Conference%20on%20Machine
      Format
      • Printed

      Held At:

      1. Bristol University Printed
    12. Search result: 12.

      Title

      Proceedings / International Conference on Machine Learning and Cybernetics.

      Author
      • International Conference on Machine Learning and Cybernetics.
      Other titles
      • Machine learning and cybernetics
      • Proceedings of ... International Conference on Machine Learning and Cybernetics
      • International Conference on Machine Learning and Cybernetics proceedings
      Frequency
      • Annual
      Published
      • Piscataway, NJ : Institute of Electrical and Electronics Engineers.
      ISSN
      • 2160-1348
      Notes
      • Description based on SFX database 04 April 2016.
      • Mode of access: World Wide Web.
      • Description based on print.
      Genre
      • Conference publication
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Proceedings
      Format
      • Printed
      • Online

      Held At:

      1. University College London Online Printed
    13. Search result: 13.

      Title

      Workshop on managing large-scale systems via the analysis of system logs and the application of machine learning techniques.

      In
      Published
      • Association for Computing Machinery 2011
      Physical description
      p. 20-46.
      Genre
      • Conference publication
      • text
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Workshop%20on%20managing%20large-scale%20systems%20via%20the%20analysis
      Format
      • Printed

      Held At:

      1. British Library Printed
    14. Search result: 14.

      Title

      Machine learning for image-based classification of Alzheimer's disease.

      Author
      • Gray, Katherine Rachel [author]
      Published
      • [Great Britain] : Imperial College London 2012
      Physical description
      1 online resource
      Notes
      • Thesis (Ph.D.)--Imperial College London, 2012.
      • Includes bibliographical references.
      Summary
      • Abstract: Imaging biomarkers for Alzheimer's disease are important for improved diagnosis and monitoring, as well as drug discovery. Automated image-based classification of individual patients could provide valuable support for clinicians. This work investigates machine learning methods aimed at the early identification of Alzheimer's disease, and prediction of progression in mild cognitive impairment. Data are obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL). Multi-region analyses of cross-sectional and longitudinal FDG-PET images from ADNI are performed. Information extracted from FDG-PET images acquired at a single timepoint is used to achieve classification results comparable with those obtained using data from research-quality MRI, or cerebrospinal fluid biomarkers. The incorporation of longitudinal information results in improved classification performance. Changes in multiple biomarkers may provide complementary information for the diagnosis and prognosis of Alzheimer's disease. A multi-modality classification framework based on random forest-derived similarities is applied to imaging and biological data from ADNI. Random forests provide consistent similarities for multiple modalities, facilitating the combination of different types of features. Classification based on the combination of MRI volumes, FDG-PET intensities, cerebrospinal fluid biomarkers, and genetics out-performs classification based on any individual modality. Multi-region analysis of MRI acquired at a single timepoint is used to show volumetric differences in cognitively normal individuals differing in amyloid-based risk status for the development of Alzheimer's disease. Reduced volumes in temporo-parietal and orbito-frontal regions in high-risk individuals from both ADNI and AIBL could be indicative of early signs of neurodegeneration. This suggests that volumetric MRI can reveal structural brain changes preceding the onset of clinical symptoms. Taken together, these results suggest that image-based classification can support diagnosis in Alzheimer's disease and preceding stages. Future work may lead to more finely meshed prognostic data that may be useful clinically and for research.
      Other names
      • Rueckert, Daniel.
      • Hammers, Alexander.
      • Imperial College, London [degree granting institution]
      Genre
      • Bibliography
      • text
      • Thesis
      Internet Resources
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Machine%20learning%20for%20image-based%20classification%20of
      Format
      • Printed
      • Online

      Held At:

      1. British Library Online Printed
    15. Search result: 15.

      Title

      Introduction to machine learning and its application in chemistry. / [By Fechner, Nikolas]

      Author
      • Fechner, Nikolas
      Genre
      • Videorecording
      Internet Resources
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Introduction%20to%20machine%20learning%20and%20its%20application
      Format
      • Visual

      Held At:

      1. Manchester University Visual
    16. Search result: 16.

      Cover image

      Title

      Signal processing theory, audio, acoustic and speech processing, and machine learning / editors Paulo S.R. Diniz, Program of Electrical Engineering and the Department of Electronics and Computer Engineering, COPPE/Poli, Universidade Federal do Rio de Janeiro, Brazil, Johan A.K. Sukyens, KU Leuven, ESAT-SCD/SISTA, Leuven (Heverlee), Belgium, Rama Chellappa, Department of Electrical and Computer Engineering and Center for Automation Research, University of Maryland, College Park, MD, USA, Sergios Theodoridis, Department of Informatics & Telecommunications, University, Athens, Greece.

      Series
      • Academic Press library in signal processing ; volume 1
      Edition
      First edition.
      Published
      • Amsterdam : Academic Press 2014
      Physical description
      li, 1506 pages : illustrations (black and white) ; 25 cm.
      ISBN
      • 9780123965028
      Notes
      • Includes bibliographical references and index.
      Summary
      • This first volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in machine learning and advanced signal processing theory. With this reference source you will: * Quickly grasp a new area of research * Understand the underlying principles of a topic and its application* Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved * Quick tutorial reviews of important and emerging topics of research in machine learning* Presents core principles in signal processing theory and shows their applications* Reference content on core principles, technologies, algorithms and applications * Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge * Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic
      Other names
      • Diniz, Paulo Sergio Ramirez 1956- [editor of compilation]
      • Suykens, Johan A. K. [editor of compilation]
      • Chellappa, Rama [editor of compilation]
      • Theodoridis, Sergios 1951- [editor of compilation]
      Genre
      • Bibliography
      • Illustrated
      • text
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Signal%20processing%20theory%2C%20audio%2C%20acoustic%20and%20speech
      Format
      • Printed

      This is a merged record. View the constituent records by format:

      16.1

      Title

      Signal processing theory, audio, acoustic and speech processing, and machine learning / editors Paulo S.R. Diniz, Program of Electrical Engineering and the Department of Electronics and Computer Engineering, COPPE/Poli, Universidade Federal do Rio de Janeiro, Brazil, Johan A.K. Sukyens, KU Leuven, ESAT-SCD/SISTA, Leuven (Heverlee), Belgium, Rama Chellappa, Department of Electrical and Computer Engineering and Center for Automation Research, University of Maryland, College Park, MD, USA, Sergios Theodoridis, Department of Informatics & Telecommunications, University, Athens, Greece.

      Series
      • Academic Press library in signal processing ; volume 1
      Edition
      First edition.
      Published
      • Amsterdam : Academic Press 2014
      Physical description
      li, 1506 pages : illustrations (black and white) ; 25 cm.
      ISBN
      • 9780123965028
      Notes
      • Includes bibliographical references and index.
      Other names
      • Diniz, Paulo Sergio Ramirez 1956- [editor of compilation]
      • Suykens, Johan A. K. [editor of compilation]
      • Chellappa, Rama [editor of compilation]
      • Theodoridis, Sergios 1951- [editor of compilation]
      Genre
      • Bibliography
      • Illustrated
      • text
      Format
      • Printed

      Held At:

      1. British Library Printed

      16.2

      Title

      Signal processing theory, audio, acoustic and speech processing, and machine learning / editors Paulo S.R. Diniz, Program of Electrical Engineering and the Department of Electronics and Computer Engineering, COPPE/Poli, Universidade Federal do Rio de Janeiro, Brazil, Johan A.K. Sukyens, KU Leuven, ESAT-SCD/SISTA, Leuven (Heverlee), Belgium, Rama Chellappa, Department of Electrical and Computer Engineering and Center for Automation Research, University of Maryland, College Park, MD, USA, Sergios Theodoridis, Department of Informatics & Telecommunications, University, Athens, Greece.

      Series
      • Academic Press library in signal processing ; volume 1
      Edition
      First edition.
      Published
      • Amsterdam : Academic Press 2014
      Physical description
      li, 1506 pages : illustrations (black and white) ; 25 cm.
      ISBN
      • 9780123965028
      Notes
      • Includes bibliographical references and index.
      Other names
      • Diniz, Paulo Sergio Ramirez 1956- [editor of compilation]
      • Suykens, Johan A. K. [editor of compilation]
      • Chellappa, Rama [editor of compilation]
      • Theodoridis, Sergios 1951- [editor of compilation]
      Genre
      • Bibliography
      • Illustrated
      • text
      Format
      • Printed

      16.3

      Title

      Signal processing theory, audio, acoustic and speech processing, and machine learning / editors Paulo S.R. Diniz, Program of Electrical Engineering and the Department of Electronics and Computer Engineering, COPPE/Poli, Universidade Federal do Rio de Janeiro, Brazil, Johan A.K. Sukyens, KU Leuven, ESAT-SCD/SISTA, Leuven (Heverlee), Belgium, Rama Chellappa, Department of Electrical and Computer Engineering and Center for Automation Research, University of Maryland, College Park, MD, USA, Sergios Theodoridis, Department of Informatics & Telecommunications, University, Athens, Greece.

      Series
      • Academic Press library in signal processing ; volume 1
      Edition
      First edition.
      Published
      • Amsterdam : Academic Press 2014
      Physical description
      li, 1506 pages : illustrations (black and white) ; 25 cm.
      ISBN
      • 9780123965028
      Notes
      • Includes bibliographical references and index.
      Other names
      • Diniz, Paulo Sergio Ramirez 1956- [editor of compilation]
      • Suykens, Johan A. K. [editor of compilation]
      • Chellappa, Rama [editor of compilation]
      • Theodoridis, Sergios 1951- [editor of compilation]
      Genre
      • Bibliography
      • Illustrated
      • text
      Format
      • Printed

      Held At:

      1. Trinity College Dublin Printed
    17. Search result: 17.

      Title

      International Conference on Machine Learning and Computing.

      Other titles
      • Machine Learning and Computing, International Conference on
      Frequency
      • Unknown
      Published
      • IEEE.
      Internet Resources
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=International%20Conference%20on%20Machine%20Learning%20and%20Computing.
      Format
      • Printed
      • Online

      This is a merged record. View the constituent records by format:

      17.1

      Title

      International Conference on Machine Learning and Computing

      Other titles
      • Machine Learning and Computing, International Conference on
      Frequency
      • Unknown
      Published
      • IEEE
      Internet Resources
      Format
      • Printed

      Held At:

      1. Imperial College Printed

      17.2

      Title

      International Conference on Machine Learning and Computing.

      Other titles
      • Machine Learning and Computing, International Conference on
      Frequency
      • Unknown
      Published
      • IEEE
      Internet Resources
      Format
      • Printed

      Held At:

      1. Leicester University Printed

      17.3

      Title

      International Conference on Machine Learning and Computing.

      Other titles
      • Machine Learning and Computing, International Conference on
      Frequency
      • Unknown
      Published
      • IEEE
      Internet Resources
      Format
      • Printed

      Held At:

      1. Manchester University Printed

      17.4

      Title

      International Conference on Machine Learning and Computing.

      Other titles
      • Machine Learning and Computing, International Conference on
      Frequency
      • Unknown
      Published
      • IEEE.
      Internet Resources
      Format
      • Printed

      Held At:

      1. Sheffield University Printed

      17.5

      Title

      International Conference on Machine Learning and Computing.

      Other titles
      • Machine Learning and Computing, International Conference on
      Frequency
      • Unknown
      Published
      • IEEE
      Format
      • Online

      Held At:

      1. York University Online
    18. Search result: 18.

      Title

      A data‐driven, machine learning framework for optimal pest management in cotton.

      In
      Published
      • [Place of publication not identified] : John Wiley & Sons 2016
      Physical description
      1 online resource
      Notes
      • In: Ecosphere, Vol. 7, no. 3 ( 2016), p.n/a-n/a.
      Summary
      • AbstractDespite the significant effects of agricultural pest management on crop yield, profit, environmental quality, and sustainability, farmers oftentimes lack data‐driven decision support to help optimize pest management strategies. To address this need, we curated a comprehensive data set that consists of pest, pest management, and yield information from 1498 commercial cotton crops in California's San Joaquin Valley between 1997 and 2008. Using this data set, we built a Markov decision process model to identify the optimal management policy of a key cotton pest,Lygus hesperus, that balances the tradeoff between yield loss and the cost of pesticide applications. Our results show that pesticide applications targetingL. hesperusare only economically optimal during the first 2 weeks of June, and pesticide applications were associated with increased risk of an unprofitable harvest. About 46% of the observations in our data set involved at least one pesticide application outside of this optimal window, demonstrating the need for a data‐driven approach to crop management. Sensitivity analyses on parameter perturbations and reduced data set sizes suggest that our methodology provides a robust policy‐making tool, even in noisy data sets.
      Other names
      • Meisner, Matthew H.
      • Rosenheim, Jay A.
      • Tagkopoulos, Ilias.
      • Peters, D. P. C.
      Genre
      • text
      Internet Resources
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=data%E2%80%90driven%2C%20machine%20learning%20framework%20for%20optimal
      Format
      • Printed
      • Online

      Held At:

      1. National Library of Scotland Online Printed
    19. Search result: 19.

      Title

      Eigen-based machine learning techniques for complex and hyper-complex processing.

      Author
      • Enshaeifar, Shirin [author]
      Published
      • [Great Britain] : University of Surrey 2016
      Physical description
      1 online resource
      Notes
      • Thesis (Ph.D.)--University of Surrey, 2016.
      • Includes bibliographical references.
      • University of Surrey
      Other names
      • Cheong Took, Clive [degree supervisor]
      • University of Surrey [degree granting institution]
      Genre
      • Bibliography
      • text
      • Thesis
      Internet Resources
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Eigen-based%20machine%20learning%20techniques%20for%20complex
      Format
      • Printed
      • Online

      Held At:

      1. British Library Online Printed
    20. Search result: 20.

      Title

      Automated algorithmic trading : machine learning and agent-based modelling in complex adaptive financial markets.

      Author
      • Booth, Ash [author]
      Published
      • [Great Britain] : University of Southampton 2016
      Physical description
      1 online resource
      Notes
      • Thesis (Ph.D.)--University of Southampton, 2016.
      • Includes bibliographical references.
      Other names
      • University of Southampton [degree granting institution]
      Genre
      • Bibliography
      • text
      • Thesis
      Internet Resources
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Automated%20algorithmic%20tradingmachine%20learning%20and%20agent-based
      Format
      • Printed
      • Online

      Held At:

      1. British Library Online Printed
    21. Search result: 21.

      Title

      Global supply chain optimization : a machine learning perspective to improve caterpillar's logistics operations.

      Author
      • Veluscek, Marco [author]
      Published
      • [Great Britain] : Brunel University London 2016
      Physical description
      1 online resource
      Notes
      • Thesis (Ph.D.)--Brunel University London, 2016.
      • Includes bibliographical references.
      • Caterpillar Inc.
      Other names
      • Kalganova, T. [degree supervisor]
      • Broomhead, P. [degree supervisor]
      • Brunel University [degree granting institution]
      Genre
      • Bibliography
      • text
      • Thesis
      Internet Resources
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Global%20supply%20chain%20optimizationa%20machine%20learning
      Format
      • Printed
      • Online

      Held At:

      1. British Library Online Printed
    22. Search result: 22.

      Title

      Using machine learning and computer simulations to analyse neuronal activity in the cerebellar nuclei during absence epilepsy.

      Author
      • Alva, Parimala [author]
      Published
      • [Great Britain] : University of Hertfordshire 2016
      Physical description
      1 online resource
      Notes
      • Thesis (Ph.D.)--University of Hertfordshire, 2016.
      • Includes bibliographical references.
      Other names
      • University of Hertfordshire [degree granting institution]
      Genre
      • Bibliography
      • text
      • Thesis
      Internet Resources
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Using%20machine%20learning%20and%20computer%20simulations%20to
      Format
      • Printed
      • Online

      Held At:

      1. British Library Online Printed
    23. Search result: 23.

      Cover image

      Title

      Machine learning in medical imaging / edited by Fei Wang, Dinggang Shen, Pingkun Yan, Kenji Suzuki.

      Author
      • Wang, Fei. [editor]
      Series
      • Lecture Notes in Computer Science 0302-9743 ; 7588
      • Lecture Notes in Computer Science, 7588. 0302-9743
      Published
      • Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer 2012
      ISBN
      • 9783642354281
      Notes
      • System details: Use the Find It button to locate the e-book.
      Summary
      • This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Medical Imaging, MLMI 2012, held in conjunction with MICCAI 2012, in Nice, France, in October 2012. The 33 revised full papers presented were carefully reviewed and selected from 67 submissions. The main aim of this workshop is to help advance the scientific research within the broad field of machine learning in medical imaging. It focuses on major trends and challenges in this area, and it presents work aimed to identify new cutting-edge techniques and their use in medical imaging.
      Other names
      • Shen, Dinggang. [editor]
      • Yan, Pingkun. [editor]
      • Suzuki, Kenji. [editor]
      • Elsevier.
      Related item
      Genre
      • text
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Machine%20learning%20in%20medical%20imaging
      Format
      • Printed
      • Online

      Held At:

      1. Royal Holloway, University of London Online Printed
    24. Search result: 24.

      Title

      Transmembrane protein structure prediction using machine learning.

      Author
      • Nugent, T. C. O. [author]
      Published
      • [Great Britain] : University College London (University of London) 2010
      Physical description
      1 online resource
      Notes
      • Thesis (Ph.D.)--University College London (University of London), 2010.
      • Includes bibliographical references.
      Summary
      • Abstract: This thesis describes the development and application of machine learning-based methods for the prediction of alpha-helical transmembrane protein structure from sequence alone. It is divided into six chapters. Chapter 1 provides an introduction to membrane structure and dynamics, membrane protein classes and families, and membrane protein structure prediction. Chapter 2 describes a topological study of the transmembrane protein CLN3 using a consensus of bioinformatic approaches constrained by experimental data. Mutations in CLN3 can cause juvenile neuronal ceroid lipofuscinosis, or Batten disease, an inherited neurodegenerative lysosomal storage disease affecting children, therefore such studies are important for directing further experimental work into this incurable illness. Chapter 3 explores the possibility of using biologically meaningful signatures described as regular expressions to influence the assignment of inside and outside loop locations during transmembrane topology prediction. Using this approach, it was possilbe to modify a recent topology prediction method leading to an improvement of 6% prediction accuracy using a standard data set. Chapter 4 describes the development of a novel support vector machine-based topology predictor that integrates both signal peptide and re-entrant helix prediction, benchmarked with full cross-validation on a novel data set of sequences with known crystal structures. The method achieves state-of-the-art performance in predicting topology and discriminating between globular and transmembrane proteins. We also present the results of applying these tools to a number of complete genomes. Chapter 5 describes a novel approach to predict lipid exposure, residue contacts, helix-helix interactions and finally the optimal helical packing arrangement of transmembrane proteins. It is based on two support vector machine classifiers that predict per residue lipid exposure and residue contacts, which are used to determine helix-helix interaction with up to 65% accuracy. The method is also able to discriminate native from decoy helical packing arrangements with up to 70% accuracy. Finally, a force-directed algorithm is employed to construct the optimal helical packing arrangement which demonstrates success for proteins containing up to 13 transmembrane helices. The final chapter summarises the major contributions of this thesis to biology, before future perspectives for TM protein structure prediction are discussed.
      Other names
      • University College, London [degree granting institution]
      Genre
      • Bibliography
      • text
      • Thesis
      Internet Resources
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Transmembrane%20protein%20structure%20prediction%20using%20machine
      Format
      • Printed
      • Online

      Held At:

      1. British Library Online Printed
    25. Search result: 25.

      Title

      Exploiting structure defined by data in machine learning : some new analyses.

      Author
      • Lever, G. [author]
      Published
      • [Great Britain] : University College London (University of London) 2011
      Physical description
      1 online resource
      Notes
      • Thesis (Ph.D.)--University College London (University of London), 2011.
      • Includes bibliographical references.
      Summary
      • Abstract: This thesis offers some new analyses and presents some new methods for learning in the context of exploiting structure defined by data – for example, when a data distribution has a submanifold support, exhibits cluster structure or exists as an object such as a graph. 1. We present a new PAC-Bayes analysis of learning in this context, which is sharp and in some ways presents a better solution than uniform convergence methods. The PAC-Bayes prior over a hypothesis class is defined in terms of the unknown true risk and smoothness of hypotheses w.r.t. the unknown data-generating distribution. The analysis is “localized” in the sense that complexity of the model enters not as the complexity of an entire hypothesis class, but focused on functions of ultimate interest. Such bounds are derived for various algorithms including SVMs. 2. We consider an idea similar to the p-norm Perceptron for building classifiers on graphs. We define p-norms on the space of functions over graph vertices and consider interpolation using the pnorm as a smoothness measure. The method exploits cluster structure and attains a mistake bound logarithmic in the diameter, compared to a linear lower bound for standard methods. 3. Rademacher complexity is related to cluster structure in data, quantifying the notion that when data clusters we can learn well with fewer examples. In particular we relate transductive learning to cluster structure in the empirical resistance metric. 4. Typical methods for learning over a graph do not scale well in the number of data points – often a graph Laplacian must be inverted which becomes computationally intractable for large data sets. We present online algorithms which, by simplifying the graph in principled way, are able to exploit the structure while remaining computationally tractable for large datasets. We prove state-of-the-art performance guarantees.
      Other names
      • University College, London [degree granting institution]
      Genre
      • Bibliography
      • text
      • Thesis
      Internet Resources
      Direct Link
      http://copac.jisc.ac.uk/id/37425820?style=html&title=Exploiting%20structure%20defined%20by%20data%20in%20machine%20learningsome
      Format
      • Printed
      • Online

      Held At:

      1. British Library Online Printed

    Search Within Results:

    Display options: