14.2.14.1 Bayesian Clustering, Bayes Classifier

Chapter Contents (Back)
Bayes Nets. Bayes Classifier. See also Bayesian Learning, Bayes Network, Bayesian Networks. See also Bayesian Networks, Bayes Nets. 0202

Beisner, H.M.,
A recursive Bayesian approach to pattern recognition,
PR(1), No. 1, July 1968, pp. 13-31.
WWW Link. 0309
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Basu, J.P., Odell, P.L.,
Effect of intraclass correlation among training samples on the misclassification probabilities of bayes procedure,
PR(6), No. 1, June 1974, pp. 13-16.
WWW Link. 0309
See also Effect of autocorrelated training samples on Bayes' probabilities of misclassification. BibRef

Decell, Jr., H.P.[Henry P.], Odell, P.L., Coberly, W.A.[William A.],
Linear dimension reduction and Bayes classification,
PR(13), No. 3, 1981, pp. 241-243.
WWW Link. 0309
BibRef

Tsokos, C.P.[Chris P.], Welch, R.L.W.,
Bayes discrimination with mean square error loss,
PR(10), No. 2, 1978, pp. 113-123.
WWW Link. 0309
BibRef

Tubbs, J.D.,
Effect of autocorrelated training samples on Bayes' probabilities of misclassification,
PR(12), No. 6, 1980, pp. 351-354.
WWW Link. 0309
extends: See also Effect of intraclass correlation among training samples on the misclassification probabilities of bayes procedure. BibRef

Tubbs, J.D., Coberly, W.A., Young, D.M.,
Linear dimension reduction and Bayes classification with unknown population parameters,
PR(15), No. 3, 1982, pp. 167-172.
WWW Link. 0309
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van Ness, J.W.[John W.],
On the Dominance of Non-Parametric Bayes Rule Discriminant Algorithms in High Dimensions,
PR(12), No. 6, 1980, pp. 355-368.
WWW Link. BibRef 8000

Postaire, J.G.,
An unsupervised Bayes classifier for normal patterns based on marginal densities analysis,
PR(15), No. 2, 1982, pp. 103-111.
WWW Link. 0309
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Jajuga, K.[Krzysztof],
Bayes classification rule for the general discrete case,
PR(19), No. 5, 1986, pp. 413-415.
WWW Link. 0309
BibRef

Toussaint, G.T.[Godfried T.],
Bayes classification rule for the general discrete case,
PR(20), No. 4, 1987, pp. 411.
WWW Link. 0309
BibRef

Kurzynski, M.W.[Marek W.],
On the multistage Bayes classifier,
PR(21), No. 4, 1988, pp. 355-365.
WWW Link. 0309
See also On the Identity of Optimal Strategies for Multistage Classifiers. See also optimal strategy of a tree classifier, The. BibRef

Garber, F.D., and Djouadi, A.,
Bounds on the Bayes Classification Error Based on Pairwise Risk Functions,
PAMI(10), No. 2, March 1988, pp. 281-288.
IEEE DOI BibRef 8803

Hwang, S.Y.[Shu-Yuen],
Two heuristics for arranging the order of feature-extraction operations in recursive Bayesian decision rule,
PR(23), No. 12, 1990, pp. 1389-1392.
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Carhart, G.W.[Gary W.], Draayer, B.F.[Bret F.], Giles, M.K.[Michael K.],
Optical-Pattern Recognition Using Bayesian Classification,
PR(27), No. 4, April 1994, pp. 587-606.
WWW Link. BibRef 9404

Ruiz, A.[Alberto],
A Nonparametric Bound for the Bayes Error,
PR(28), No. 6, June 1995, pp. 921-930.
WWW Link. 0401
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Avi-Itzhak, H., Diep, T.A.,
Arbitrarily Tight Upper and Lower Bounds on the Bayesian Probability of Error,
PAMI(18), No. 1, January 1996, pp. 89-91.
IEEE DOI BibRef 9601

Xu, L.,
Bayesian Ying-Yang Machine, Clustering and Number of Clusters,
PRL(18), No. 11-13, November 1997, pp. 1167-1178. 9806
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Hurn, M.A., Mardia, K.V., Hainsworth, T.J., Kirkbride, J., Berry, E.,
Bayesian fused classification of medical images,
MedImg(15), No. 6, December 1996, pp. 850-858.
IEEE Top Reference. 0203
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Mardia, K.V., Hainsworth, T.J., Kirkbride, J.,
Hierarchical Bayesian Classification of Multimodal Medical Images,
MMBIA96(Bayesian Analysis) BibRef 9600

Gorte, B., Stein, A.,
Bayesian Classification and Class Area Estimation of Satellite Images Using Stratification,
GeoRS(36), No. 3, May 1998, pp. 803-812.
IEEE Top Reference. 9806
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Rajan, J.J., Rayner, P.J.W., Godsill, S.J.,
Bayesian Approach to Parameter Estimation and Interpolation of Time Varying Autoregressive Processes Using the Gibbs Sampler,
VISP(144), No. 4, August 1997, pp. 249-256. 9806
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Sanjaygopel, S., Hebert, T.J.,
Bayesian Pixel Classification Using Spatially Variant Finite Mixtures and the Generalized EM Algorithm,
IP(7), No. 7, July 1998, pp. 1014-1028.
IEEE DOI 9807
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Roberts, S.J.[Stephen J.], Husmeier, D.[Dirk], Rezek, I.[Iead], Penny, W.D.[William D.],
Bayesian Approaches to Gaussian Mixture Modeling,
PAMI(20), No. 11, November 1998, pp. 1133-1142.
IEEE DOI 9811
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Williams, C.K.I., Barber, D.,
Bayesian Classification With Gaussian Processes,
PAMI(20), No. 12, December 1998, pp. 1342-1351.
IEEE DOI BibRef 9812

Horiuchi, T.[Takahiko],
Decision Rule for Pattern Classification by Integrating Interval Feature Values,
PAMI(20), No. 4, April 1998, pp. 440-448.
IEEE DOI 9806
Bayes Nets. BibRef

Horiuchi, T.[Takahiko],
Pattern Classification Method by Integrating Interval Feature Values,
ICDAR97(847-850).
IEEE DOI 9708
BibRef

Warrender, C.E.[Christina E.], Augusteijn, M.F.[Marijke F.],
Fusion of image classifications using Bayesian techniques with Markov random fields,
JRS(20), No. 10, July 1999, pp. 1987. BibRef 9907

Foggia, P.[Pasquale], Sansone, C.[Carlo], Tortorella, F., Vento, M.[Mario],
Multiclassification: reject criteria for the Bayesian combiner,
PR(32), No. 8, August 1999, pp. 1435-1447.
WWW Link. BibRef 9908

Cordella, L.P., Foggia, P.[Pasquale], Sansone, C.[Carlo], Tortorella, F., Vento, M.,
Classification reliability and its use in multi-classifier systems,
CIAP97(I: 46-53).
Springer DOI 9709
BibRef

Foggia, P.[Pasquale], Percannella, G.[Gennaro], Sansone, C.[Carlo], Vento, M.[Mario],
The Impact of Reliability Evaluation on a Semi-supervised Learning Approach,
CIAP09(249-258).
Springer DOI 0909
BibRef
Earlier:
Evaluating Classification Reliability for Combining Classifiers,
CIAP07(711-716).
IEEE DOI 0709
BibRef

Cordella, L.P., Foggia, P., Sansone, C., Vento, M.,
Learning structural shape descriptions from examples,
PRL(23), No. 12, October 2002, pp. 1427-1437.
Elsevier DOI 0206
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Marrocco, C.[Claudio], Molinara, M.[Mario], Tortorella, F.[Francesco],
Exploiting AUC for optimal linear combinations of dichotomizers,
PRL(27), No. 8, June 2006, pp. 900-907.
WWW Link. 0605
BibRef
Earlier:
AUC-Based Linear Combination of Dichotomizers,
SSPR06(714-722).
Springer DOI 0608
BibRef
Earlier:
Estimating the ROC Curve of Linearly Combined Dichotomizers,
CIAP05(778-785).
Springer DOI 0509
Two-class classifiers; ROC curve; Multiple classifier systems; Linear combiners See also Towards a Linear Combination of Dichotomizers by Margin Maximization. BibRef

Antos, A.[Andras], Devroye, L.[Luc], Gyoerfi, L.[Laszlo],
Lower Bounds for Bayes Error Estimation,
PAMI(21), No. 7, July 1999, pp. 643-645.
IEEE DOI BibRef 9907

Davis, R.[Robert], Prieditis, A.[Armand],
Designing Optimal Sequential Experiments for a Bayesian Classifier,
PAMI(21), No. 3, March 1999, pp. 193-201.
IEEE DOI Generate better classifiers using more computation. BibRef 9903

Rangarajan, A.[Anand], Hsiao, I.T.[Ing-Tsung], Gindi, G.[Gene],
A Bayesian Joint Mixture Framework for the Integration of Anatomical Information in Functional Image Reconstruction,
JMIV(12), No. 3, June 2000, pp. 199-217.
DOI Link 0003
BibRef

Rueda, L.G.[Luis G.], Oommen, B.J.[B. John],
On Optimal Pairwise Linear Classifiers for Normal Distributions: The Two-Dimensional Case,
PAMI(24), No. 2, February 2002, pp. 274-280.
IEEE DOI 0202
Bayesian Clustering. Linear classifier is a pair of straight lines. BibRef

Rueda, L.G.[Luis G.], Oommen, B.J.[B. John],
On Optimal Pairwise Linear Classifiers for Normal Distributions: The D-Dimensional Case,
PR(36), No. 1, January 2003, pp. 13-23.
WWW Link. 0210
See also Linear dimensionality reduction by maximizing the Chernoff distance in the transformed space. BibRef

Rueda, L.G.[Luis G.],
Selecting the best hyperplane in the framework of optimal pairwise linear classifiers,
PRL(25), No. 1, January 2004, pp. 49-62.
WWW Link. 0311
BibRef

Rueda, L.G.[Luis G.],
An efficient approach to compute the threshold for multi-dimensional linear classifiers,
PR(37), No. 4, April 2004, pp. 811-826.
WWW Link. 0403
BibRef

Rueda, L.G.[Luis G.],
A one-dimensional analysis for the probability of error of linear classifiers for normally distributed classes,
PR(38), No. 8, August 2005, pp. 1197-1207.
WWW Link. 0505
See also comment on: A one-dimensional analysis for the probability of error of linear classifiers for normally distributed classes by Rueda, A. BibRef

Oommen, B.J.[B. John], Rueda, L.G.[Luis G.],
Stochastic learning-based weak estimation of multinomial random variables and its applications to pattern recognition in non-stationary environments,
PR(39), No. 3, March 2006, pp. 328-341.
WWW Link. 0601
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Forsyth, D.A., Haddon, J., Ioffe, S.,
The Joy of Sampling,
IJCV(41), No. 1-2, January-February 2001, pp. 109-134.
DOI Link Sampling for Bayesian models applied to structure from motion and color constancy. 0105
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Huang, H.J.[Hung-Ju], Hsu, C.N.[Chun-Nan],
Bayesian classification for data from the same unknown class,
SMC-B(32), No. 2, April 2002, pp. 137-145.
IEEE Top Reference. 0205
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Zribi, M.[Mourad],
Non-parametric and unsupervised Bayesian classification with Bootstrap sampling,
IVC(22), No. 1, January 2004, pp. 1-8.
WWW Link. 0401
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Zribi, M.[Mourad],
Unsupervised Bayesian image segmentation using orthogonal series,
JVCIR(18), No. 6, December 2007, pp. 496-503.
WWW Link. 0711
Unsupervised Bayesian image segmentation; Orthogonal series estimator; Stochastic and Nonparametric Expectation-Maximization BibRef

Zribi, M.[Mourad], Ghorbel, F.[Faouzi],
An Unsupervised and Non-Parametric Bayesian Classifier,
PRL(24), No. 1-3, January 2003, pp. 97-112.
Elsevier DOI 0211
BibRef
Earlier:
An unsupervised and non-parametric Bayesian Image segmentation,
CIAP95(423-428).
Springer DOI 9509
BibRef

Vass, G.G.[György G.], Daoudi, M.[Mohamed], Ghorbel, F.[Faouzi],
Optimization methods in multilayer classifier networks for automatic control of lamellibranch larva growth,
CIAP97(II: 220-227).
Springer DOI 9709
BibRef

Eastman, J.R., Laney, R.M.,
Bayesian Soft Classification for Sub-Pixel Analysis: A Critical Evaluation,
PhEngRS(68), No. 11, November 2002, pp. 1149-1154. Fuzzy training sites improve the accuracy of the Bayesian classification procedure by increasing the degree of overlap between parent distributions.
WWW Link. 0304
BibRef

Pernkopf, F.[Franz], O'Leary, P.[Paul],
Floating search algorithm for structure learning of Bayesian network classifiers,
PRL(24), No. 15, November 2003, pp. 2839-2848.
WWW Link. 0308
BibRef
Earlier:
Feature Selection for Classification Using Genetic Algorithms with a Novel Encoding,
CAIP01(161 ff.).
Springer DOI 0210
BibRef

Pernkopf, F.[Franz],
Bayesian network classifiers versus selective k-NN classifier,
PR(38), No. 1, January 2005, pp. 1-10.
WWW Link. 0410
BibRef

Pernkopf, F.[Franz], Wohlmayr, M.[Michael], Tschiatschek, S.[Sebastian],
Maximum Margin Bayesian Network Classifiers,
PAMI(34), No. 3, March 2012, pp. 521-532.
IEEE DOI 1201
Conjugate gradient optimization. Maintain normalization on constraints of the Bayesian network BibRef

Mutsam, N.[Nikolaus], Pernkopf, F.[Franz],
Maximum margin hidden Markov models for sequence classification,
PRL(77), No. 1, 2016, pp. 14-20.
Elsevier DOI 1606
Hidden Markov models BibRef

Tschiatschek, S., Pernkopf, F.,
On Bayesian Network Classifiers with Reduced Precision Parameters,
PAMI(37), No. 4, April 2015, pp. 774-785.
IEEE DOI 1503
Bayes methods BibRef

Pernkopf, F.[Franz], Wohlmayr, M.[Michael],
Stochastic margin-based structure learning of Bayesian network classifiers,
PR(46), No. 2, February 2013, pp. 464-471.
Elsevier DOI 1210
Bayesian network classifier; Discriminative learning; Maximum margin learning; Structure learning BibRef

Raymer, M.L., Doom, T.E., Kuhn, L.A., Punch, W.F.,
Knowledge discovery in medical and biological datasets using a hybrid Bayes classifier/evolutionary algorithm,
SMC-B(33), No. 5, October 2003, pp. 802-813.
IEEE Abstract. 0310
BibRef

Thomaz, C.E., Gillies, D.F., Feitosa, R.Q.,
A New Covariance Estimate for Bayesian Classifiers in Biometric Recognition,
CirSysVideo(14), No. 2, February 2004, pp. 214-223.
IEEE Abstract. 0403
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Storvik, G., Fjortoft, R., Solberg, A.H.S.,
A Bayesian Approach to Classification of Multiresolution Remote Sensing Data,
GeoRS(43), No. 3, March 2005, pp. 539-547.
IEEE Abstract. 0501
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Kwoh, C.K.[Chee-Keong], Gillies, D.F.[Duncan Fyfe],
Estimating the initial values of unobservable variables in visual probabilistic networks,
CAIP95(326-333).
Springer DOI 9509
BibRef

Aksoy, S., Koperski, K., Tusk, C., Marchisio, G., Tilton, J.C.,
Learning Bayesian Classifiers for Scene Classification With a Visual Grammar,
GeoRS(43), No. 3, March 2005, pp. 581-589.
IEEE Abstract. 0501
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Hand, D.J., and Yu, K.,
Idiot's Bayes: Not so Stupid After All?,
Statistical Review(69), 2001, pp. 385-398. BibRef 0100

Jamain, A.[Adrien], Hand, D.J.[David J.],
The Naive Bayes Mystery: A classification detective story,
PRL(26), No. 11, August 2005, pp. 1752-1760.
WWW Link. 0506
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Zhang, H.[Harry], Su, J.[Jiang],
Learning probabilistic decision trees for AUC,
PRL(27), No. 8, June 2006, pp. 892-899.
WWW Link. Naive Bayes; Ranking 0605
BibRef

Nadarajah, S.[Saralees], Kotz, S.[Samuel],
A comment on: 'A one-dimensional analysis for the probability of error of linear classifiers for normally distributed classes' by Rueda,
PR(40), No. 5, May 2007, pp. 1632-1633.
WWW Link. 0702
See also one-dimensional analysis for the probability of error of linear classifiers for normally distributed classes, A. BibRef

Shi, X.J.[Xiao-Jin], Manduchi, R.[Roberto],
On the Bayes fusion of visual features,
IVC(25), No. 11, 1 November 2007, pp. 1748-1758.
WWW Link. 0709
Image classification; Bayes fusion; Color; Texture BibRef

Sicard, R.[Rudy], Artieres, T.[Thierry], Petit, E.[Eric],
Learning iteratively a classifier with the Bayesian Model Averaging Principle,
PR(41), No. 3, March 2008, pp. 930-938.
WWW Link. 0711
Bayesian model averaging; Point estimate approximation; Naieve Bayes classifier; Statistical classification BibRef

Hernandez-Lobato, D.[Daniel], Hernandez-Lobato, J.M.[Jose Miguel],
Bayes Machines for binary classification,
PRL(29), No. 10, 15 July 2008, pp. 1466-1473.
WWW Link. 0711
Kernel methods; Approximate inference; Bayesian methods; Expectation Propagation; Bayes Point Machines; Bayes Machines BibRef

Agrawal, R.K., Bala, R.[Rajni],
Incremental Bayesian classification for multivariate normal distribution data,
PRL(29), No. 13, 1 October 2008, pp. 1873-1876.
WWW Link. 0804
Bayesian classification; Multivariate normal distribution; Sequential classification; Feature selection BibRef

Agrawal, R.K., Bala, R.[Rajni], Bala, M.[Manju],
Discriminant Function Revisited for Incremental Learning,
ICCVGIP08(435-441).
IEEE DOI 0812
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Damoulas, T.[Theodoros], Girolami, M.A.[Mark A.],
Pattern recognition with a Bayesian kernel combination machine,
PRL(30), No. 1, 1 January 2009, pp. 46-54.
WWW Link. 0811
Classification; Kernel combination; MCMC; Probit regression; Bayesian inference; Information integration BibRef

Damoulas, T.[Theodoros], Girolami, M.A.[Mark A.],
Combining feature spaces for classification,
PR(42), No. 11, November 2009, pp. 2671-2683.
Elsevier DOI 0907
Variational Bayes approximation; Multiclass classification; Kernel combination; Hierarchical Bayes; Bayesian inference; Ensemble learning; Multi-modal modelling; Information integration BibRef

Liao, W.H.[Wen-Hui], Ji, Q.A.[Qi-Ang],
Learning Bayesian network parameters under incomplete data with domain knowledge,
PR(42), No. 11, November 2009, pp. 3046-3056.
Elsevier DOI 0907
BibRef
Earlier:
Exploiting qualitative domain knowledge for learning Bayesian network parameters with incomplete data,
ICPR08(1-4).
IEEE DOI 0812
Bayesian network parameter learning; Missing data; EM algorithm; Facial action unit (AU) recognition BibRef

Jiang, L.X.[Liang-Xiao],
Random one-dependence estimators,
PRL(32), No. 3, 1 February 2011, pp. 532-539.
Elsevier DOI 1101
Naive Bayes; One-dependence estimators; Random selection; Classification; Class probability estimation; Ranking BibRef

Schlueter, R.[Ralf], Nussbaum-Thom, M.[Markus], Ney, H.[Hermann],
Does the Cost Function Matter in Bayes Decision Rule?,
PAMI(34), No. 2, February 2012, pp. 292-301.
IEEE DOI 1112
Applied to various tasks. Analysis of Bayesian techniques. BibRef

Silva, J.F.[Jorge F.], Narayanan, S.S.[Shrikanth S.],
On signal representations within the Bayes decision framework,
PR(45), No. 5, May 2012, pp. 1853-1865.
Elsevier DOI 1201
Signal representation; Minimum risk decision; Bayes decision framework; Estimation-approximation error tradeoff; complexity regularization; Mutual information; Decision trees; Linear discriminant analysis BibRef

Ducinskas, K.[Kestutis], Stabingiene, L.[Lijana], Stabingis, G.[Giedrius],
Image Classification Based on Bayes Discriminant Functions,
Procedia Env. Sci(7), 2011, pp. 218-223
Elsevier DOI 1301
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And: Retraction information for second reference:
Application of Bayes linear discriminant functions in image classification,
PRL(35), No. 3, 1 February 2013, pp. 358.
Elsevier DOI 1301
Retracted Reference, do not use: PRL(33), No. 3, 1 February 2012, pp. 278-282. Image classification; Gaussian random fields; Actual error rate; Bayes discriminant function. Adding spatial information. BibRef

Ružic, T.[Tijana], Pižurica, A.[Aleksandra], Philips, W.[Wilfried],
Neighborhood-consensus message passing as a framework for generalized iterated conditional expectations,
PRL(33), No. 3, 1 February 2012, pp. 309-318.
Elsevier DOI 1201
Markov random fields; Bayesian inference; Iterated conditional modes; Message passing BibRef

Liao, W.Z.[Wen-Zhi], Pizurica, A.[Aleksandra], Philips, W.[Wilfried], Pi, Y.[Youguo],
A fast iterative kernel PCA feature extraction for hyperspectral images,
ICIP10(1317-1320).
IEEE DOI 1009
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Boullé, M.[Marc],
Functional data clustering via piecewise constant nonparametric density estimation,
PR(45), No. 12, December 2012, pp. 4389-4401.
Elsevier DOI 1208
Functional data; Distributional data; Exploratory analysis; Clustering; Bayesianism; Model selection; Density estimation BibRef

Zheng, S.F.[Song-Feng], Liu, W.X.[Wei-Xiang],
Functional gradient ascent for Probit regression,
PR(45), No. 12, December 2012, pp. 4428-4437.
Elsevier DOI 1208
Probit regression; Classification; Functional gradient ascent; Boosting BibRef

Dalton, L.A.[Lori A.], Dougherty, E.R.[Edward R.],
Optimal classifiers with minimum expected error within a Bayesian framework - Part I: Discrete and Gaussian models,
PR(46), No. 5, May 2013, pp. 1301-1314.
Elsevier DOI 1302
Bayesian estimation; Classification; Error estimation; Genomics; Minimum mean-square estimation; Small samples BibRef

Dalton, L.A.[Lori A.], Dougherty, E.R.[Edward R.],
Optimal classifiers with minimum expected error within a Bayesian framework - Part II: Properties and performance analysis,
PR(46), No. 5, May 2013, pp. 1288-1300.
Elsevier DOI 1302
Bayesian estimation; Classification; Error estimation; Genomics; Minimum mean-square estimation; Small samples BibRef

Nielsen, F.,
An Information-Geometric Characterization of Chernoff Information,
SPLetters(20), No. 3, March 2013, pp. 269-272.
IEEE DOI 1303
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Burduk, R.[Robert],
Classifier fusion with interval-valued weights,
PRL(34), No. 14, 2013, pp. 1623-1629.
Elsevier DOI 1308
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Earlier:
Probability Error in Bayes Optimal Classifier with Intuitionistic Fuzzy Observations,
ICIAR09(359-368).
Springer DOI 0907
Classifier fusion BibRef

Feng, G.[Guang], Zhang, J.D.[Jia-Dong], Liao, S.S.[Stephen Shaoyi],
A novel method for combining Bayesian networks, theoretical analysis, and its applications,
PR(47), No. 5, 2014, pp. 2057-2069.
Elsevier DOI 1402
Bayesian networks combination BibRef

Wang, X.Z.[Xi-Zhao], He, Y.L.[Yu-Lin], Wang, D.D.,
Non-Naive Bayesian Classifiers for Classification Problems With Continuous Attributes,
Cyber(44), No. 1, January 2014, pp. 21-39.
IEEE DOI 1402
Bayes methods BibRef

Besson, O., Dobigeon, N., Tourneret, J.Y.,
Joint Bayesian Estimation of Close Subspaces from Noisy Measurements,
SPLetters(21), No. 2, February 2014, pp. 168-171.
IEEE DOI 1402
Bayes methods BibRef

Ruiz, P., Mateos, J., Camps-Valls, G., Molina, R., Katsaggelos, A.K.,
Bayesian Active Remote Sensing Image Classification,
GeoRS(52), No. 4, April 2014, pp. 2186-2196.
IEEE DOI 1403
Bayes methods BibRef

Stein, M., Castaneda, M., Mezghani, A., Nossek, J.A.,
Information-Preserving Transformations for Signal Parameter Estimation,
SPLetters(21), No. 7, July 2014, pp. 866-870.
IEEE DOI 1405
Bayes methods BibRef

Knowles, D.A., Ghahramani, Z.,
Pitman-Yor Diffusion Trees for Bayesian Hierarchical Clustering,
PAMI(37), No. 2, February 2015, pp. 271-289.
IEEE DOI 1502
Bayes methods BibRef

Archambeau, C.[Cedric], Lakshminarayanan, B., Bouchard, G.,
Latent IBP Compound Dirichlet Allocation,
PAMI(37), No. 2, February 2015, pp. 321-333.
IEEE DOI 1502
Analytical models Indian buffet process (IBP). BibRef

Gershman, S.J., Frazier, P.I., Blei, D.M.,
Distance Dependent Infinite Latent Feature Models,
PAMI(37), No. 2, February 2015, pp. 334-345.
IEEE DOI 1502
Analytical models BibRef

Foti, N.J., Williamson, S.A.,
A Survey of Non-Exchangeable Priors for Bayesian Nonparametric Models,
PAMI(37), No. 2, February 2015, pp. 359-371.
IEEE DOI 1502
Bayesian nonparametrics BibRef

Doshi-Velez, F., Pfau, D., Wood, F., Roy, N.,
Bayesian Nonparametric Methods for Partially-Observable Reinforcement Learning,
PAMI(37), No. 2, February 2015, pp. 394-407.
IEEE DOI 1502
Bayes methods BibRef

Deisenroth, M.P., Fox, D., Rasmussen, C.E.,
Gaussian Processes for Data-Efficient Learning in Robotics and Control,
PAMI(37), No. 2, February 2015, pp. 408-423.
IEEE DOI 1502
Approximation methods BibRef

Gilboa, E., Saatci, Y., Cunningham, J.P.,
Scaling Multidimensional Inference for Structured Gaussian Processes,
PAMI(37), No. 2, February 2015, pp. 424-436.
IEEE DOI 1502
Additives BibRef

Orbanz, P., Roy, D.M.,
Bayesian Models of Graphs, Arrays and Other Exchangeable Random Structures,
PAMI(37), No. 2, February 2015, pp. 437-461.
IEEE DOI 1502
Analytical models BibRef

Palla, K., Knowles, D.A., Ghahramani, Z.,
Relational Learning and Network Modelling Using Infinite Latent Attribute Models,
PAMI(37), No. 2, February 2015, pp. 462-474.
IEEE DOI 1502
Atmospheric modeling BibRef

Xu, Z., Yan, F., Qi, Y.,
Bayesian Nonparametric Models for Multiway Data Analysis,
PAMI(37), No. 2, February 2015, pp. 475-487.
IEEE DOI 1502
Bayes methods BibRef

Blomstedt, P., Tang, J., Xiong, J., Granlund, C., Corander, J.,
A Bayesian Predictive Model for Clustering Data of Mixed Discrete and Continuous Type,
PAMI(37), No. 3, March 2015, pp. 489-498.
IEEE DOI 1502
Bayes methods BibRef

Sun, S.J.[Shu-Jin], Zhong, P.[Ping], Xiao, H.T.[Huai-Tie], Wang, R.S.[Run-Sheng],
Active Learning With Gaussian Process Classifier for Hyperspectral Image Classification,
GeoRS(53), No. 4, April 2015, pp. 1746-1760.
IEEE DOI 1502
Bayes methods BibRef

Sun, L.[Lei], Toh, K.A.[Kar-Ann], Lin, Z.P.[Zhi-Ping],
A center sliding Bayesian binary classifier adopting orthogonal polynomials,
PR(48), No. 6, 2015, pp. 2013-2028.
Elsevier DOI 1503
Binary classification BibRef

Klarreich, E.[Erica],
In Search of Bayesian Inference,
CACM(58), No. 1, January 2015, pp. 21-24.
DOI Link 1503
BibRef

Broumand, A.[Ariana], Esfahani, M.S.[Mohammad Shahrokh], Yoon, B.J.[Byung-Jun], Dougherty, E.R.[Edward R.],
Discrete optimal Bayesian classification with error-conditioned sequential sampling,
PR(48), No. 11, 2015, pp. 3766-3782.
Elsevier DOI 1506
Optimal Bayesian classifier BibRef

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Kim, Y.D., Jang, T., Han, B., Choi, S.,
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Qi, Y.[Yuan], Picard, R.W.,
Context-sensitive Bayesian classifiers and application to mouse pressure pattern classification,
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Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
K-Means Clustering .


Last update:Sep 18, 2017 at 11:34:11