14.5.6 Bayesian Learning

Smith, A.F.M., and Spiegelhalter, D.J.,
Bayes factors and choice criteria for linear models,
RoyalStat(B42), 1980, pp. 213-220. BibRef 8000

Belforte, G., Bona, B., and Tempo, R.,
Conditional Allocation and Stopping Rules in Bayesian Pattern Recognition,
PAMI(8), No. 4, July 1986, pp. 502-511. BibRef 8607

Stirling, W.C., and Swindlehurst, A.L.,
Decision-Directed Multivariate Empirical Bayes Classification with Nonstationary Priors,
PAMI(9), No. 5, September 1987, pp. 644-660. BibRef 8709

Lowe, D.G., and Webb, A.R.,
Optimized Feature Extraction and the Bayes Decision in Feed-Forward Classifier Networks,
PAMI(13), No. 4, April 1991, pp. 355-364.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9104

Domingos, P., and Pazzani, M.,
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss,
MachLearn(29), 1997, pp. 103-130. BibRef 9700

Friedman, N., Geiger, D., and Goldszmid, M.,
Bayesian Network Classifiers,
MachLearn(29), 2997, No. 2, pp. 131-163. BibRef 0000

Grenander, U., Srivastava, A., and Miller, M.I.,
Asymptotic performance analysis of Bayesian object recognition,
IT(46), No. 4, April 2000, pp. 1658-1666. BibRef 0004

Magni, P., Bellazzi, R., de Nicolao, G.,
Bayesian Function Learning Using MCMC Methods,
PAMI(20), No. 12, December 1998, pp. 1319-1331.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9812

Li, T.F.[Tze Fen],
Bayes empirical Bayes approach to unsupervised learning of parameters in pattern recognition,
PR(33), No. 2, February 2000, pp. 333-340.
WWW Version. 0001 BibRef

Li, T.F.[Tze Fen], Chang, S.C.[Shui-Ching],
Classification on defective items using unidentified samples,
PR(38), No. 1, January 2005, pp. 51-58.
WWW Version. 0410 BibRef

Guo, G.D.[Guo-Dong], Ma, S.D.[Song-De],
Bayesian learning, global competition and unsupervised image segmentation,
PRL(21), No. 2, February 2000, pp. 107-116. 0003 BibRef

Yuille, A.L.[Alan L.], Coughlan, J.M.[James M.],
Fundamental Limits of Bayesian Inference: Order Parameters and Phase Transitions for Road Tracking,
PAMI(22), No. 2, February 2000, pp. 160-173.
IEEE Abstract. IEEE Top Reference.
WWW Version. 0003 Road Following. BibRef

Rangarajan, A., Coughlan, J.M., Yuille, A.L.,
A bayesian network framework for relational shape matching,
ICCV03(671-678).
WWW Version. 0311 BibRef

Sarkar, S.[Sudeep], Chavali, S.[Srikanth],
Modeling Parameter Space Behavior of Vision Systems Using Bayesian Networks,
CVIU(79), No. 2, August 2000, pp. 185-223. 0008
WWW Version. BibRef

Lampinen, J., Vehtari, A., Leinonen, K.,
Using Bayesian Neural Network to Solve the Inverse Problem in Electrical Impedance Tomography,
SCIA99(Neural Nets). BibRef 9900

Paulus, D., Hornegger, J., Niemann, H.,
A Framework for Statistical 3-D Object Recognition,
PRL(18), No. 11-13, November 1997, pp. 1153-1157.
Postscript Version. 9806 BibRef

Hornegger, J.[Joachim], Niemann, H.[Heinrich],
Probabilistic Modeling and Recognition of 3-D Objects,
IJCV(39), No. 3, September-October 2000, pp. 229-251.
WWW Version. 0101 BibRef

Hornegger, J., Paulus, D., and Niemann, H.,
Probabilistic Modeling in Computer Vision,
HCVA99(Vol 2, 817-854).
Postscript Version. BibRef 9900

Hornegger, J., Niemann, H.,
Statistical Learning, Localization, and Identification of Objects,
ICCV95(914-919).
WWW Version.
WWW Version. BibRef 9500

Hornegger, J., Niemann, H.,
A Bayesian Approach to Learn and Classify 3D Objects from Intensity Images,
ICPR94(B:557-559).
WWW Version. BibRef 9400

Hornegger, J.[Joachim], Welker, V.[Volkmar], Niemann, H.[Heinrich],
Localization and classification based on projections,
PR(35), No. 6, June 2002, pp. 1225-1235.
WWW Version. 0203 BibRef

Nock, R.[Richard], Sebban, M.[Marc],
A Bayesian boosting theorem,
PRL(22), No. 3-4, March 2001, pp. 413-419.
HTML Version. 0105 BibRef

Peņa, J.M.[Jose Manuel], Lozano, J.A.[Jose Antonio], Larraņaga, P.[Pedro], Inza, I.[Iņaki],
Dimensionality Reduction in Unsupervised Learning of Conditional Gaussian Networks,
PAMI(23), No. 6, June 2001, pp. 590-603.
IEEE Abstract. IEEE Top Reference.
WWW Version. 0106Unsupervised learning of conditional Gaussian networks, reject features that have low correlation with others. BibRef

Kupinski, M.A., Edwards, D.C., Giger, M.L., Metz, C.E.,
Ideal observer approximation using bayesian classification neural networks,
MedImg(20), No. 9, September 2001, pp. 886-899.
IEEE Top Reference. 0110 See also Ideal Observers and Optimal ROC Hypersurfaces in N-Class Classification. BibRef

Yin, H., Allinson, N.M.,
Bayesian self-organising map for Gaussian mixtures,
VISP(148), No. 4, August 2001, pp. 234-240. 0201 BibRef

Hand, D.J., and Yu, K.,
Idiot's Bayes: Not so Stupid After All?,
Statistical Review(69), 2001, pp. 385-398. BibRef 0100

Mitra, S.K.[Suman K.], Lee, T.W.[Te-Won], Goldbaum, M.[Michael],
A Bayesian network based sequential inference for diagnosis of diseases from retinal images,
PRL(26), No. 4, March 2005, pp. 459-470.
WWW Version. 0501 BibRef

Gurwicz, Y.[Yaniv], Lerner, B.[Boaz],
Bayesian network classification using spline-approximated kernel density estimation,
PRL(26), No. 11, August 2005, pp. 1761-1771.
WWW Version. 0506 BibRef
Earlier:
Rapid spline-based kernel density estimation for bayesian networks,
ICPR04(III: 700-703).
WWW Version. 0409 BibRef

Gurwicz, Y.[Yaniv], Lerner, B.[Boaz],
Bayesian Class-Matched Multinet Classifier,
SSPR06(145-153).
WWW Version. 0608 BibRef

Yehezkel, R.[Raanan], Lerner, B.[Boaz],
Bayesian Network Structure Learning by Recursive Autonomy Identification,
SSPR06(154-162).
WWW Version. 0608 BibRef

Webb, G.I., Boughton, J., and Wang, Z.,
Not So Naive Bayes: Aggregating One-Dependence Estimators,
MachLearn(58), 2005, No. 1, pp. 5-24. BibRef 0500

Li, F.F.[Fei-Fei], Fergus, R.[Rob], Perona, P.[Pietro],
One-Shot Learning of Object Categories,
PAMI(28), No. 4, April 2006, pp. 594-611.
WWW Version. 0604 BibRef
Earlier:
A bayesian approach to unsupervised one-shot learning of object categories,
ICCV03(1134-1141).
WWW Version. 0311 BibRef

Wang, G.[Gang], Zhang, Y.[Ye], Li, F.F.[Fei-Fei],
Using Dependent Regions for Object Categorization in a Generative Framework,
CVPR06(II: 1597-1604).
WWW Version. 0606 BibRef

Li, F.F.[Fei-Fei], Fergus, R.[Rob], Perona, P.[Pietro],
Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories,
CVIU(106), No. 1, April 2007, pp. 59-70.
WWW Version. 0704 BibRef
Earlier: GenModel04(178).
WWW Version. 0406 BibRef

Object recognition; Categorization; Generative model; Incremental learning; Bayesian model

Li, F.F.[Fei-Fei], Perona, P.[Pietro],
A Bayesian Hierarchical Model for Learning Natural Scene Categories,
CVPR05(II: 524-531).
WWW Version. 0507 BibRef

Kuncheva, L.I.[Ludmila I.],
On the optimality of Naīve Bayes with dependent binary features,
PRL(27), No. 7, May 2006, pp. 830-837.
WWW Version. Statistical pattern recognition; Naive Bayes classifier (NB); Optimality of NB; Dependent binary features 0604 BibRef

Ji, S.[Shihao], Krishnapuram, B.[Balaji], Carin, L.[Lawrence],
Variational Bayes for Continuous Hidden Markov Models and Its Application to Active Learning,
PAMI(28), No. 4, April 2006, pp. 522-532.
WWW Version. 0604 BibRef

Ji, S.[Shihao], Carin, L.[Lawrence],
Cost-sensitive feature acquisition and classification,
PR(40), No. 5, May 2007, pp. 1474-1485.
WWW Version. 0702Cost-sensitive classification; Partially observable Markov decision processes (POMDP); Hidden Markov models (HMMs); Variational Bayes (VB) BibRef

Williams, D.[David], Liao, X.[Xuejun], Xue, Y.[Ya], Carin, L.[Lawrence], Krishnapuram, B.[Balaji],
On Classification with Incomplete Data,
PAMI(29), No. 3, March 2007, pp. 427-436.
WWW Version. 0702Feature vectors have missing features. Supervised regression algorithm. BibRef

Johansson, M., Olofsson, T.,
Bayesian Model Selection for Markov, Hidden Markov, and Multinomial Models,
SPLetters(14), No. 2, February 2007, pp. 129-132.
WWW Version. 0703 BibRef

Galan, S.F.,
Belief updating in Bayesian networks by using a criterion of minimum time,
PRL(29), No. 4, 1 March 2008, pp. 465-482.
WWW Version. 0711Bayesian network; Variable elimination; Elimination ordering; Clustering algorithms; Triangulation; Criterion of minimum time BibRef

Kuncheva, L.I.[Ludmila I.], Hoare, Z.[Zoe],
Error-Dependency Relationships for the Naīve Bayes Classifier with Binary Features,
PAMI(30), No. 4, April 2008, pp. 735-740.
WWW Version. 0803 BibRef

Jain, A.K., Mallapragada, P.K.[Pavan K.], Law, M.[Martin],
Bayesian Feedback in Data Clustering,
ICPR06(III: 374-378).
WWW Version. 0609 BibRef

Martinez-Arroyo, M.[Miriam], Sucar, L.E.[L. Enrique],
Learning an Optimal Naive Bayes Classifier,
ICPR06(III: 1236-1239).
WWW Version. 0609 BibRef
And: ICPR06(IV: 958).
WWW Version. 0609 BibRef

Kanaujia, A.[Atul], Metaxas, D.[Dimitris],
Learning Multi-category Classification in Bayesian Framework,
ACCV06(I:255-264).
WWW Version. 0601 See also Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference. BibRef

Lo, B.P.L., Thiemjarus, S., Yang, G.Z.[Guang-Zhong],
Adaptive Bayesian networks for video processing,
ICIP03(I: 889-892).
IEEE Abstract. IEEE Top Reference. 0312Adapt, or learn, while processing. BibRef

Fergus, R.[Rob], Perona, P.[Pietro], Zisserman, A.[Andrew],
A Sparse Object Category Model for Efficient Learning and Complete Recognition,
CLOR06(443-461).
WWW Version. 0711 BibRef
And: Fergus, R., Perona, P., Zisserman, A.,
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition,
CVPR05(I: 380-387).
WWW Version. 0507 BibRef

Takebe, H.[Hiroaki], Kurokawa, K.[Koji], Katsuyama, Y.[Yutaka], Naoi, S.[Satoshi],
A Learning Pseudo Bayes Discriminant Method Based on Difference Distribution of Feature Vectors,
DAS02(134 ff.).
HTML Version. 0303 BibRef

Souafi-Bensafi, S., Parizeau, M., Le Bourgeois, F., Emptoz, H.,
Bayesian networks classifiers applied to documents,
ICPR02(I: 483-486).
WWW Version. 0211 BibRef
Earlier:
Logical labeling using Bayesian networks,
ICDAR01(832-836).
WWW Version. 0109 BibRef

Baesens, B., Egmont-Petersen, M., Castelo, R., Vanthienen, J.,
Learning Bayesian network classifiers for credit scoring using Markov chain Monte Carlo search,
ICPR02(III: 49-52).
WWW Version. 0211 BibRef

Vailaya, A., Jain, A.K.,
Reject Option for VQ-based Bayesian Classification,
ICPR00(Vol II: 48-51).
WWW Version.
HTML Version. 0009 BibRef

Vailaya, A.[Aditya], Jain, A.K.[Anil K.],
Incremental Learning for Bayesian Classification of Images,
ICIP99(II:585-589).
IEEE Abstract. IEEE Top Reference. BibRef 9900

Utschick, W., Nossek, J.A.,
Bayesian Adaptation of Hidden Layers in Boolean Feedforward Neural Networks,
ICPR96(IV: 229-233).
WWW Version. 9608(Technical Univ. of Munich, D) BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Genetic Algorithms, Genetic Programming .