Statistical Mechanics of Learning

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Cambridge University Press, Mar 29, 2001 - Computers - 329 pages
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The effort to build machines that are able to learn and undertake tasks such as datamining, image processing and pattern recognition has led to the development of artificial neural networks in which learning from examples may be described and understood. The contribution to this subject made over the past decade by researchers applying the techniques of statistical mechanics is the subject of this book. The authors provide a coherent account of various important concepts and techniques that are currently only found scattered in papers, supplement this with background material in mathematics and physics, and include many examples and exercises.
  

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Contents

II
1
III
4
IV
8
V
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VI
14
VIII
18
IX
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X
27
LIV
155
LV
159
LVI
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LVII
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LVIII
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LIX
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LX
171
LXI
176

XI
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XII
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XIII
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XIV
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XV
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XVI
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XVII
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XVIII
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XX
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XXI
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XXVIII
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XXIX
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XXX
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XXXI
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XXXII
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XXXIII
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XXXIV
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XXXV
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XXXVI
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XXXVII
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XXXVIII
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XXXIX
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XLI
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XLIII
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XLV
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XLVII
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XLVIII
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XLIX
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L
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LI
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LII
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LIII
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LXII
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LXIII
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LXIV
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LXV
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LXX
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LXXX
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LXXXIX
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XC
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XCI
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XCII
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XCIII
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XCIV
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XCV
289
XCVI
291
XCVII
300
XCVIII
304
XCIX
310
C
313
CI
327
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Page 318 - K. Rose, E. Gurewitz, and GC Fox, "Statistical mechanics and phase transitions in clustering," Physical Review Letters, vol.

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