13.3.5.2 Boltzmann Machine, Simulated Annealing, and Related Topics

Kirpatrick, S., Gelatt, Jr., C.D., and Vecchi, M.P.,
Optimization by Simulated Annealing,
Science(220), 13 May 1983, pp. 671-680. Iterative optimization method that is described in terms used in cooling metal. Reducing the energy level slowly to go to some reduced energy state, resetting the state by random events, etc. BibRef 8305

Geman, S., and Geman, D.,
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images,
PAMI(6), No. 6, November 1984, pp. 721-741.
PDF Version. BibRef 8411

Ackley, D.H., Hinton, G.E., and Sejnowski, T.J.,
A Learning Algorithm for Boltzmann Machines,
CogSci(9), 1985, pp. 147-169. Reprinted: BibRef 8500 RCV87(522-533). The massively parallel, simple processing element description of the relaxation process. BibRef

Hinton, G.E.[Geoffrey E.], and Sejnowski, T.J.[Terrence J.],
Optimal Perceptual Inference,
CVPR83(448-453). Different formulation of probabilistic relaxation and how to avoid non global minima (energy states). BibRef 8300

Sejnowski, T.J., and Hinton, G.E.,
Separating Figure from Ground with a Boltzmann Machine,
VBCC1987. BibRef 8700

Dyan, P., Hinton, G.E., Neal, R.M., and Zemel, R.S.,
The Helmholtz Machine,
NeurComp(7), No. 7, 1995, pp. 889-904. BibRef 9500

Carnevali, P., Coletti, L., Patarnello, S.,
Image Processing by Simulated Annealing,
IBMRD(29), No. 6, November 1985, pp. 569-579. BibRef 8511

Szu, H.H., Hartley, R.L.,
Nonconvex Optimization by Fast Simulated Annealing,
PIEEE(75), 1987, pp. 1538-1540. BibRef 8700

Klein, R.W.[Raymond W.], Dubes, R.C.[Richard C.],
Experiments in projection and clustering by simulated annealing,
PR(22), No. 2, 1989, pp. 213-220.
WWW Version. 0309
BibRef

Li, X.B.[Xiao-Bo], Dubes, R.C.[Richard C.],
A probabilistic measure of similarity for binary data in pattern recognition,
PR(22), No. 4, 1989, pp. 397-409.
WWW Version. 0309
BibRef

Atkin, G.K., Bowcock, J.E., Queen, N.M.,
Solution of a distributed deterministic parallel network using simulated annealing,
PR(22), No. 4, 1989, pp. 461-466.
WWW Version. 0309
BibRef

Selim, S.Z.[Shokri Z.], Alsultan, K.,
A simulated annealing algorithm for the clustering problem,
PR(24), No. 10, 1991, pp. 1003-1008.
WWW Version. 0401
BibRef

Brown, D.E.[Donald E.], Huntley, C.L.[Christopher L.],
A practical application of simulated annealing to clustering,
PR(25), No. 4, April 1992, pp. 401-412.
WWW Version. 0401
BibRef

d'Anjou, A., Grana, M., Torrealdea, F.J., and Hernandez, M.C.,
Solving Satisfiability via Boltzmann Machines,
PAMI(15), No. 5, May 1993, pp. 514-521.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9305

Granville, V., Krivanek, M., Rasson, J.P.,
Simulated Annealing: A Proof of Convergence,
PAMI(16), No. 6, June 1994, pp. 652-656.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9406

Storvik, G.,
A Bayesian-Approach to Dynamic Contours Through Stochastic Sampling and Simulated Annealing,
PAMI(16), No. 10, October 1994, pp. 976-986.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9410

Bongiovanni, G., Crescenzi, P., Guerra, C.,
Parallel Simulated Annealing for Shape Detection,
CVIU(61), No. 1, January 1995, pp. 60-69.
WWW Version. BibRef 9501

Guerra, C.,
Survey of parallel algorithms for structural pattern matching,
ICPR94(C:275-278).
IEEE DOI Link 9410
BibRef

Li, S.Z.,
Robustizing Robust M-Estimation Using Deterministic Annealing,
PR(29), No. 1, January 1996, pp. 159-166.
WWW Version. BibRef 9601

Taxt, T., Bolivken, E.,
Relaxation Using Models from Quantum Mechanics,
PR(24), No. 7, 1991, pp. 695-709.
WWW Version. BibRef 9100

Albizuri, F.X., d'Anjou, A., Grana, M., Lozano, J.A.,
Convergence Properties of High-Order Boltzmann Machines,
NeurNet(9), No. 9, December 1996, pp. 1561-1567. 9701
BibRef

Aleksander, I.,
Adaptive Pattern Recognition Systems and Boltzmann Machines: A Rapprochement,
PRL(6), 1987, pp. 113-120. BibRef 8700

Barhen, J.[Jacob], Protopopescu, V.[Vladimir], Reister, D.B.[David B.],
TRUST: A Deterministic Algorithm for Global Optimization,
Science(276), No. 5315, 16 May 1997, pp. 1094-1097. Global optimization that is faster and more accurate and escapes local minima. BibRef 9705

Noll, D., von Seelen, W.,
Object Recognition by Deterministic Annealing,
IVC(15), No. 11, November 1997, pp. 855-860.
WWW Version. 9712
BibRef

Noll, D., Schwarzinger, M., von Seelen, W.,
Contextual feature similarities for model-based object recognition,
ICCV93(286-290).
IEEE DOI Link 0403
BibRef

Kappen, H.J., Rodriguez, F.B.,
Mean-Field Approach to Learning in Boltzmann Machines,
PRL(18), No. 11-13, November 1997, pp. 1317-1322. 9806
BibRef

Rao, A.V.[Ajit V.], Miller, D.J.[David J.], Rose, K.[Kenneth], Gersho, A.[Allen],
A Deterministic Annealing Approach for Parsimonious Design of Piecewise Regression Models,
PAMI(21), No. 2, February 1999, pp. 159-173.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9902

Rangarajan, A.[Anand],
Self-annealing and self-annihilation: unifying deterministic annealing and relaxation labeling,
PR(33), No. 4, April 2000, pp. 635-649.
WWW Version. 0002
BibRef

Klock, H.[Hansjörg], Buhmann, J.M.[Joachim M.],
Data Visualization by Multidimensional Scaling: A Deterministic Annealing Approach,
PR(33), No. 4, April 2000, pp. 651-669.
WWW Version. 0002
BibRef

Chen, H., Murray, A.F.,
Continuous restricted Boltzmann machine with an implementable training algorithm,
VISP(150), No. 3, June 2003, pp. 153-158.
IEEE Abstract. IEEE Top Reference. 0308
BibRef

Thompson, D.R., Bilbro, G.L.,
Sample-Sort Simulated Annealing,
SMC-B(35), No. 3, June 2005, pp. 625-632.
IEEE DOI Link 0508
BibRef

Luo, Q.A.[Qi-Ang], Yang, W.[Wenqiang], Liu, P.Y.[Pu-Yin],
Promoter recognition based on the Interpolated Markov Chains optimized via simulated annealing and genetic algorithm,
PRL(27), No. 9, July 2006, pp. 1031-1036.
WWW Version. Simulated annealing 0605
BibRef

Yang, X.L., Song, Q., Zhang, W.B.,
Kernel-based deterministic annealing algorithm for data clustering,
VISP(153), No. 5, October 2006, pp. 557-568.
WWW Version. 0702
BibRef

Ma, J.W.[Jin-Wen], Liu, J.F.[Jian-Feng],
The BYY annealing learning algorithm for Gaussian mixture with automated model selection,
PR(40), No. 7, July 2007, pp. 2029-2037.
WWW Version. 0704
Bayesian Ying-Yang (BYY) learning; Gaussian mixture; Automated model selection; Simulated annealing; Unsupervised image segmentation BibRef

Ma, J.W.[Jin-Wen], Liu, J.F.[Jian-Feng], Ren, Z.J.[Zhi-Jie],
Parameter estimation of Poisson mixture with automated model selection through BYY harmony learning,
PR(42), No. 11, November 2009, pp. 2659-2670.
Elsevier DOI Link
WWW Version. 0907
Bayesian Ying-Yang (BYY) harmony learning; Poisson mixture; Gradient learning algorithm; Automated model selection; Texture classification BibRef

Ma, J.W.[Jin-Wen], He, X.F.[Xue-Feng],
A fast fixed-point BYY harmony learning algorithm on Gaussian mixture with automated model selection,
PRL(29), No. 6, 15 April 2008, pp. 701-711.
WWW Version. 0803
Bayesian Ying-Yang (BYY) system; Harmony learning; Gaussian mixture; Automated model selection; Fixed-point BibRef

Gall, J.[Jürgen], Potthoff, J.[Jürgen], Schnörr, C.[Christoph], Rosenhahn, B.[Bodo], Seidel, H.P.[Hans-Peter],
Interacting and Annealing Particle Filters: Mathematics and a Recipe for Applications,
JMIV(28), No. 1, May 2007, pp. 1-18.
Springer DOI Link 0710
BibRef

Gall, J.[Juergen], Rosenhahn, B.[Bodo], Seidel, H.P.[Hans-Peter],
Drift-free tracking of rigid and articulated objects,
CVPR08(1-8).
IEEE DOI Link 0806
BibRef
Earlier:
Clustered Stochastic Optimization for Object Recognition and Pose Estimation,
DAGM07(32-41).
Springer DOI Link 0709
BibRef
Earlier:
Robust Pose Estimation with 3D Textured Models,
PSIVT06(84-95).
Springer DOI Link 0612
BibRef

Gedeon, T.[Tomas], Parker, A.E.[Albert E.], Campion, C.[Collette], Aldworth, Z.[Zane],
Annealing and the normalized N-cut,
PR(41), No. 2, February 2008, pp. 592-606.
WWW Version. 0711
Clustering; Annealing; Normalized N-cut BibRef

Saha, S.[Sriparna], Bandyopadhyay, S.[Sanghamitra],
A new multiobjective simulated annealing based clustering technique using stability and symmetry,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Saha, S.[Sriparna], Bandyopadhyay, S.[Sanghamitra],
A multiobjective simulated annealing based fuzzy-clustering technique with symmetry for pixel classification in remote sensing imagery,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Mancera, L.[Luis], Portilla, J.[Javier],
Non-convex sparse optimization through deterministic annealing and applications,
ICIP08(917-920).
IEEE DOI Link 0810
BibRef

Jung, H.Y.[Ho Yub], Lee, K.M.[Kyoung Mu], Lee, S.U.[Sang Uk],
Window Annealing over Square Lattice Markov Random Field,
ECCV08(II: 307-320).
Springer DOI Link 0810
BibRef

Mohebi, A.[Azadeh], Liu, Y.[Ying], Fieguth, P.W.[Paul W.],
Hierarchical Sampling with Constraints,
ICIAR09(23-32).
Springer DOI Link 0907
BibRef
Earlier: A1, A3, Only:
Constrained Sampling Using Simulated Annealing,
ICIAR07(198-209).
Springer DOI Link 0708
BibRef

Mohebi, A.[Azadeh], Fieguth, P.W.[Paul W.],
Posterior Sampling of Scientific Images,
ICIAR06(I: 339-350).
Springer DOI Link 0610
in MRI, infer structures as scales not imaged by the MRI. BibRef

Sun, L.Y.[Ling-Yu], Leng, M.[Ming],
An Effective Multi-level Algorithm Based on Simulated Annealing for Bisecting Graph,
EMMCVPR07(1-12).
Springer DOI Link 0708
BibRef

Campaigne, W.R.[Wesley R.], Fieguth, P.W.[Paul W.], Alexander, S.K.[Simon K.],
Frozen-State Hierarchical Annealing,
ICIAR06(I: 41-52).
Springer DOI Link 0610
BibRef

Alexander, S.K., Fieguth, P.W., Vrscay, E.R.,
Image sampling by hierarchical annealing,
ICIP03(I: 249-252).
IEEE Abstract. IEEE Top Reference. 0312
BibRef

Jamieson, M., Fieguth, P.W., Lee, L.J.,
Parametric contour estimation by simulated annealing,
ICIP03(III: 449-452).
IEEE Abstract. IEEE Top Reference. 0312
BibRef

Yang, X.[Xulei], Song, Q.[Qing], Zhang, W.B.[Wen-Bo], Wang, Z.M.[Zhi-Min],
Clustering Spherical Shells by a Mini-Max Information Algorithm,
ACCV06(II:224-233).
Springer DOI Link 0601
BibRef

Perrin, G.[Guillaume], Descombes, X.[Xavier], Zerubia, J.B.[Josiane B.],
Adaptive Simulated Annealing for Energy Minimization Problem in a Marked Point Process Application,
EMMCVPR05(3-17).
Springer DOI Link 0601
BibRef

Ortner, M.[Mathias], Descombes, X.[Xavier], Zerubia, J.B.[Josiane B.],
Improved RJMCMC point process sampler for object detection on images by simulated annealing,
INRIARR-4900, 2003.
HTML Version. BibRef 0300

Alexander, S.K.[Simon K.], Fieguth, P.W.[Paul W.], Vrscay, E.R.[Edward R.],
Parameterized Hierarchical Annealing for Scientific Models,
ICIAR04(I: 236-243).
WWW Version. 0409
BibRef

Hirano, T., Okada, Y., Yoda, F.,
Structural Character Recognition Using Simulated Annealing,
ICDAR97(Poste) 9708
BibRef

Younes, L.,
Learning algorithms for extended models of Boltzmann machines,
ICPR94(B:602-604).
IEEE DOI Link 9410
BibRef

Matsunaga, T., Kida, H.,
A method for designing dictionary using simulated annealing,
ICPR92(II:154-187).
IEEE DOI Link 9208
BibRef

Herault, L., Horaud, R., Veillon, F., Niez, J.J.,
Symbolic Image Matching by Simulated Annealing,
BMVC90(319-324).
PDF Version. BibRef 9000

Xu, L.[Lei],
Some applications of simulated annealing to pattern recognition,
ICPR88(II: 1040-1042).
IEEE DOI Link 8811
BibRef

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Hummel and Zucker Relaxation Papers .