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1
Gaussian Processes for Machine Learning
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Gaussian Processes for Machine Learning

2005 Massachusetts Institute of Technology ;2005 MIT This content is available without a subscription. It may not be altered in any way and proper attribution is required. ;ISBN: 9780262256834 ;ISBN: 026218253X ;ISBN: 9780262182539 ;ISBN: 0262256835 ;EISBN: 9780262256834 ;EISBN: 0262256835 ;EISBN: 0262261073 ;EISBN: 9780262261074 ;DOI: 10.7551/mitpress/3206.001.0001 ;OCLC: 68194203 ;LCCallNum: QA274.4 .R37 2006eb

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2
Graphical Models, Exponential Families, and Variational Inference
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Book
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Graphical Models, Exponential Families, and Variational Inference

ISBN: 1601981767 ;ISBN: 9781601981769 ;EISBN: 1601981775 ;EISBN: 9781601981776 ;DOI: 10.1561/2200000001 ;OCLC: 923316413

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3
A DCT Statistics-Based Blind Image Quality Index
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Article
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A DCT Statistics-Based Blind Image Quality Index

IEEE signal processing letters, 2010-06, Vol.17 (6), p.583-586 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1070-9908 ;EISSN: 1558-2361 ;DOI: 10.1109/LSP.2010.2045550

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4
Online prediction of time series data with kernels
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Online prediction of time series data with kernels

IEEE transactions on signal processing, 2009-03, Vol.57 (3), p.1058-1067 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1053-587X ;EISSN: 1941-0476 ;DOI: 10.1109/TSP.2008.2009895

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5
A study of the effect of different types of noise on the precision of supervised learning techniques
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Article
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A study of the effect of different types of noise on the precision of supervised learning techniques

The Artificial intelligence review, 2010-04, Vol.33 (4), p.275-306 [Peer Reviewed Journal]

Springer Science+Business Media B.V. 2010 ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-010-9156-z

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6
A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability
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Article
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A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability

Soft computing (Berlin, Germany), 2009-08, Vol.13 (10), p.959-977 [Peer Reviewed Journal]

Springer-Verlag 2008 ;Springer-Verlag 2008. ;ISSN: 1432-7643 ;EISSN: 1433-7479 ;DOI: 10.1007/s00500-008-0392-y

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7
Multiple Classifier Systems: Second International Workshop, MCS 2001, Cambridge, UK, July 2-4, 2001 : Proceedings
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Multiple Classifier Systems: Second International Workshop, MCS 2001, Cambridge, UK, July 2-4, 2001 : Proceedings

Springer-Verlag Berlin Heidelberg 2001 ;ISSN: 0302-9743 ;ISBN: 9783540422846 ;ISBN: 3540422846 ;ISBN: 9783540829478 ;ISBN: 3540829474 ;EISSN: 1611-3349 ;EISBN: 3540482199 ;EISBN: 9783540482192 ;DOI: 10.1007/3-540-48219-9 ;OCLC: 48984598

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8
Learning CPG-based Biped Locomotion with a Policy Gradient Method: Application to a Humanoid Robot
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Article
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Learning CPG-based Biped Locomotion with a Policy Gradient Method: Application to a Humanoid Robot

The International journal of robotics research, 2008-02, Vol.27 (2), p.213-228 [Peer Reviewed Journal]

COPYRIGHT 2008 Sage Publications, Inc. ;Copyright SAGE PUBLICATIONS, INC. Feb 2008 ;ISSN: 0278-3649 ;EISSN: 1741-3176 ;DOI: 10.1177/0278364907084980

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9
The security of machine learning
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Article
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The security of machine learning

Machine learning, 2010-11, Vol.81 (2), p.121-148 [Peer Reviewed Journal]

The Author(s) 2010 ;ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-010-5188-5

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10
L 1/2 regularization
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Article
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L 1/2 regularization

Science China. Information sciences, 2010-06, Vol.53 (6), p.1159-1169 [Peer Reviewed Journal]

ISSN: 1674-733X ;EISSN: 1869-1919 ;DOI: 10.1007/s11432-010-0090-0

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11
Predicting subcellular localization of proteins for Gram‐negative bacteria by support vector machines based on n‐peptide compositions
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Predicting subcellular localization of proteins for Gram‐negative bacteria by support vector machines based on n‐peptide compositions

Protein science, 2004-05, Vol.13 (5), p.1402-1406 [Peer Reviewed Journal]

Copyright © 2004 The Protein Society ;Copyright © Copyright 2004 The Protein Society ;ISSN: 0961-8368 ;EISSN: 1469-896X ;DOI: 10.1110/ps.03479604 ;PMID: 15096640

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12
Fast Kernel Classifiers with Online and Active Learning
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Article
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Fast Kernel Classifiers with Online and Active Learning

Journal of machine learning research, 2005-09, Vol.6, p.1579-1619 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1532-4435 ;EISSN: 1533-7928

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13
Online Learning for Matrix Factorization and Sparse Coding
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Article
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Online Learning for Matrix Factorization and Sparse Coding

Journal of machine learning research, 2010-01, Vol.11 (1), p.19-60 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1532-4435 ;EISSN: 1533-7928

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14
Machine Learning: ECML 2001: 12th European Conference on Machine Learning Freiburg, Germany, September 5–7, 2001 Proceedings
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Book
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Machine Learning: ECML 2001: 12th European Conference on Machine Learning Freiburg, Germany, September 5–7, 2001 Proceedings

Springer-Verlag Berlin Heidelberg 2001 ;ISSN: 0302-9743 ;ISBN: 9783662205983 ;ISBN: 3540425365 ;ISBN: 9783540425366 ;ISBN: 366220598X ;EISSN: 1611-3349 ;EISBN: 3540447954 ;EISBN: 9783540447955 ;DOI: 10.1007/3-540-44795-4

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15
SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent
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Article
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SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent

Journal of machine learning research, 2009-07, Vol.10, p.1737-1754 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1532-4435 ;EISSN: 1533-7928

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16
A review of multi-instance learning assumptions
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Article
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A review of multi-instance learning assumptions

Knowledge engineering review, 2010-03, Vol.25 (1), p.1-25 [Peer Reviewed Journal]

Copyright © Cambridge University Press 2010 ;ISSN: 0269-8889 ;EISSN: 1469-8005 ;DOI: 10.1017/S026988890999035X

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17
Machine Learning: ECML-98: 10th European Conference on Machine Learning Chemnitz, Germany, April 21–23, 1998 Proceedings
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Book
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Machine Learning: ECML-98: 10th European Conference on Machine Learning Chemnitz, Germany, April 21–23, 1998 Proceedings

Springer-Verlag Berlin Heidelberg 1998 ;ISSN: 0302-9743 ;ISBN: 9783540644170 ;ISBN: 3662202530 ;ISBN: 3540644172 ;ISBN: 9783662202531 ;EISSN: 1611-3349 ;EISBN: 3540697810 ;EISBN: 9783540697817 ;DOI: 10.1007/BFb0026664

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18
Conditional variable importance for random forests
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Article
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Conditional variable importance for random forests

BMC bioinformatics, 2008-07, Vol.9 (1), p.307-307, Article 307 [Peer Reviewed Journal]

COPYRIGHT 2008 BioMed Central Ltd. ;Copyright © 2008 Strobl et al; licensee BioMed Central Ltd. 2008 Strobl et al; licensee BioMed Central Ltd. ;ISSN: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/1471-2105-9-307 ;PMID: 18620558

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19
Improving propensity score weighting using machine learning
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Article
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Improving propensity score weighting using machine learning

Statistics in medicine, 2010-02, Vol.29 (3), p.337-346 [Peer Reviewed Journal]

Copyright © 2009 John Wiley & Sons, Ltd. ;(c) 2009 John Wiley & Sons, Ltd. ;ISSN: 0277-6715 ;EISSN: 1097-0258 ;DOI: 10.1002/sim.3782 ;PMID: 19960510 ;CODEN: SMEDDA

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20
Automated macromolecular model building for X-ray crystallography using ARP/wARP version 7
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Article
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Automated macromolecular model building for X-ray crystallography using ARP/wARP version 7

Nature protocols, 2008-07, Vol.3 (7), p.1171-1179 [Peer Reviewed Journal]

COPYRIGHT 2008 Nature Publishing Group ;Copyright Nature Publishing Group Jul 2008 ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1754-2189 ;ISSN: 1750-2799 ;EISSN: 1750-2799 ;DOI: 10.1038/nprot.2008.91 ;PMID: 18600222

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