Komodakis, N.[Nikos],
Tziritas, G.[Georgios],
Paragios, N.[Nikos],
Performance vs computational efficiency for optimizing single and
dynamic MRFs: Setting the state of the art with primal-dual strategies,
CVIU(112), No. 1, October 2008, pp. 14-29.
WWW Version.
0810
BibRef
Earlier:
Fast, Approximately Optimal Solutions for Single and Dynamic MRFs,
CVPR07(1-8).
IEEE DOI Link
PDF Version.
0706
Code, Alignment.
WWW Version.
BibRef
Earlier: A1, A3, A2:
MRF Optimization via Dual Decomposition: Message-Passing Revisited,
ICCV07(1-8).
IEEE DOI Link
0710
Nonlinear programming techniques.
Markov random fields; Linear programming; Primal-dual schema; Discrete
optimization; Graph cuts
BibRef
Komodakis, N.[Nikos],
Paragios, N.[Nikos],
Tziritas, G.[Georgios],
MRF Energy Minimization and Beyond via Dual Decomposition,
PAMI(33), No. 3, March 2011, pp. 531-552.
IEEE DOI Link
1102
New framework for MRF optimization. First decompose into subproblems,
then combine solutions.
BibRef
Komodakis, N.[Nikos],
Efficient training for pairwise or higher order CRFs via dual
decomposition,
CVPR11(1841-1848).
IEEE DOI Link
1106
BibRef
Komodakis, N.[Nikos],
Learning to cluster using high order graphical models with latent
variables,
ICCV11(73-80).
IEEE DOI Link
1201
BibRef
Komodakis, N.[Nikos],
Paragios, N.[Nikos],
Beyond pairwise energies: Efficient optimization for higher-order MRFs,
CVPR09(2985-2992).
IEEE DOI Link
0906
BibRef
Earlier:
Beyond Loose LP-Relaxations: Optimizing MRFs by Repairing Cycles,
ECCV08(III: 806-820).
Springer DOI Link
0810
BibRef
Komodakis, N.[Nikos],
Towards More Efficient and Effective LP-Based Algorithms for MRF
Optimization,
ECCV10(II: 520-534).
Springer DOI Link
1009
BibRef
Huda, S.[Shamsul],
Yearwood, J.[John],
Togneri, R.[Roberto],
A stochastic version of Expectation Maximization algorithm for better
estimation of Hidden Markov Model,
PRL(30), No. 14, 15 October 2009, pp. 1301-1309,.
Elsevier DOI Link
WWW Version.
0909
Hidden Markov Model; Expectation Maximization; Speech recognition;
Constraint-based Evolutionary Algorithm; Stochastic EM
BibRef
Nowozin, S.[Sebastian],
Lampert, C.H.[Christoph H.],
Global Interactions In Random Field Models:
A Potential Function Ensuring Connectedness,
SIIMS(3), No. 4, 2010, pp. 1048-1074.
WWW Version.
WWW Version.
BibRef
1000
Earlier:
Global connectivity potentials for random field models,
CVPR09(818-825).
IEEE DOI Link
0906
Markov random fields; potential functions; large cliques; high-arity
interactions
BibRef
Levada, A.L.M.[Alexandre L.M.],
Mascarenhas, N.D.A.[Nelson D.A.],
Tannus, A.[Alberto],
A novel MAP-MRF approach for multispectral image contextual
classification using combination of suboptimal iterative algorithms,
PRL(31), No. 13, 1 October 2010, pp. 1795-1808.
Elsevier DOI Link
WWW Version.
1003
BibRef
Earlier:
On the asymptotic variances of Gaussian Markov Random Field model
hyperparameters in stochastic image modeling,
ICPR08(1-4).
IEEE DOI Link
0812
BibRef
And:
A novel pseudo-likelihood equation for Potts MRF model parameter
estimation in image analysis,
ICIP08(1828-1831).
IEEE DOI Link
0810
BibRef
And:
Improving Potts MRF model parameter estimation using higher-order
neighborhood systems on stochastic image modeling,
WSSIP08(385-388).
IEEE DOI Link
0806
Contextual classification; Markov random fields; Combinatorial
optimization; Maximum pseudo-likelihood; Data fusion; Classifier
combination
BibRef
Kim, W.S.[Won-Sik],
Lee, K.M.[Kyoung Mu],
A hybrid approach for MRF optimization problems: Combination of
stochastic sampling and deterministic algorithms,
CVIU(115), No. 12, December 2011, pp. 1623-1637.
Elsevier DOI Link
WWW Version.
1111
BibRef
Earlier:
Continuous Markov Random Field Optimization Using Fusion Move Driven
Markov Chain Monte Carlo Technique,
ICPR10(1364-1367).
IEEE DOI Link
1008
BibRef
Earlier:
Markov Chain Monte Carlo combined with deterministic methods for Markov
random field optimization,
CVPR09(1406-1413).
IEEE DOI Link
0906
Analysis of the issues and techniques for computation methods in
energy minimization.
Markov Chain Monte Carlo; Markov Random Field model; Energy
minimization; Optimization
BibRef
Zhu, H.[Hao],
He, Z.S.[Zhong-Shi],
Leung, H.,
Simultaneous Feature and Model Selection for Continuous Hidden Markov
Models,
SPLetters(19), No. 5, May 2012, pp. 279-282.
IEEE DOI Link
1204
BibRef
Gallagher, A.C.[Andrew C.],
Batra, D.[Dhruv],
Parikh, D.[Devi],
Inference for order reduction in Markov random fields,
CVPR11(1857-1864).
IEEE DOI Link
1106
BibRef
Batra, D.[Dhruv],
Gallagher, A.C.,
Parikh, D.[Devi],
Chen, T.H.[Tsu-Han],
Beyond trees: MRF inference via outer-planar decomposition,
CVPR10(2496-2503).
IEEE DOI Link
1006
unify approximate methods for
Maximum a posteriori (MAP) inference in Markov Random Fields.
BibRef
Zach, C.[Christopher],
Niethammer, M.[Marc],
Frahm, J.M.[Jan-Michael],
Continuous maximal flows and Wulff shapes: Application to MRFs,
CVPR09(1911-1918).
IEEE DOI Link
0906
Extend the continuous, isotropic maximal flow framework to the
anisotropic case.
BibRef
Ali, A.M.[Asem M.],
Farag, A.A.[Aly A.],
Gimel'farb, G.L.[Georgy L.],
Optimizing Binary MRFs with Higher Order Cliques,
ECCV08(III: 98-111).
Springer DOI Link
0810
Analysis of MRFs to use pairwise results at higher orders.
Energy minimization.
BibRef
Datta, R.[Ritendra],
Hu, J.Y.[Jian-Ying],
Ray, B.[Bonnie],
On efficient Viterbi decoding for hidden semi-Markov models,
ICPR08(1-4).
IEEE DOI Link
0812
BibRef
Szummer, M.[Martin],
Kohli, P.[Pushmeet],
Hoiem, D.[Derek],
Learning CRFs Using Graph Cuts,
ECCV08(II: 582-595).
Springer DOI Link
0810
BibRef
Tappen, M.F.[Marshall F.],
Utilizing Variational Optimization to Learn Markov Random Fields,
CVPR07(1-8).
IEEE DOI Link
0706
BibRef
Rother, C.[Carsten],
Kolmogorov, V.[Vladimir],
Lempitsky, V.[Victor],
Szummer, M.[Martin],
Optimizing Binary MRFs via Extended Roof Duality,
CVPR07(1-8).
IEEE DOI Link
0706
BibRef
Tiwari, S.,
Gallager, S.,
Machine learning and multiscale methods in the identification of
bivalve larvae,
ICCV03(494-500).
IEEE DOI Link
0311
BibRef
And:
Optimizing multiscale texture invariants for the identification of
bivalve larvae,
ICIP03(III: 1061-1064).
IEEE Abstract.
0312
BibRef
Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Ant Colony Optimization .