Pattern Recognition and Machine Learning

(Jeff_L) #1
INDEX 733

Hooke’s law, 580
hybrid Monte Carlo, 548
hyperparameter, 71 , 280, 311, 346, 372, 502
hyperprior, 372


I map,seeindependence map
i.i.d.,seeindependent identically distributed
ICA,seeindependent component analysis
ICM,seeiterated conditional modes
ID3, 663
identifiability, 435
image de-noising, 387
importance sampling, 525, 532
importance weights, 533
improper prior, 118 , 259, 472
imputation step, 537
imputation-posterior algorithm, 537
inactive constraint, 328, 709
incomplete data set, 440
independence map, 392
independent component analysis, 591
independent factor analysis, 592
independent identically distributed, 26 , 379
independent variables, 17
independent, identically distributed, 605
induced factorization, 485
inequality constraint, 709
inference, 38, 42
information criterion, 33
information geometry, 298
information theory, 48
input-output hidden Markov model, 633
intensive variables, 490
intrinsic dimensionality, 559
invariance, 261
inverse gamma distribution, 101
inverse kinematics, 272
inverse problem, 272
inverse Wishart distribution, 102
IP algorithm,seeimputation-posterior algorithm
IRLS,seeiterative reweighted least squares
Ising model, 389
isomap, 596
isometric feature map, 596
iterated conditional modes, 389 , 415


iterative reweighted least squares, 207 , 210, 316,
354, 672

Jacobian matrix, 247 , 264
Jensen’s inequality, 56
join tree, 416
junction tree algorithm, 392, 416

Knearest neighbours, 125
K-means clustering algorithm, 424 , 443
K-medoids algorithm, 428
Kalman filter, 304, 637
extended, 644
Kalman gain matrix, 639
Kalman smoother, 637
Karhunen-Loeve transform, 561`
Karush-Kuhn-Tucker conditions, 330, 333, 342,
710
kernel density estimator, 122 , 326
kernel function, 123, 292 , 294
Fisher, 298
Gaussian, 296
homogeneous, 292
nonvectorial inputs, 297
stationary, 292
kernel PCA, 586
kernel regression, 300, 302
kernel substitution, 292
kernel trick, 292
kinetic energy, 549
KKT,seeKarush-Kuhn-Tucker conditions
KL divergence,seeKullback-Leibler divergence
kriging,seeGaussian process
Kullback-Leibler divergence, 55 , 451, 468, 505

Lagrange multiplier, 707
Lagrange, Joseph-Louis, 329
Lagrangian, 328, 332, 341, 708
laminar flow, 678
Laplace approximation, 213 , 217, 278, 315, 354
Laplace, Pierre-Simon, 24
large margin,seemargin
lasso, 145
latent class analysis, 444
latent trait model, 597
latent variable, 84, 364 , 430, 559
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