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Volumn 1, Issue January, 2014, Pages 640-648

On the convergence rate of decomposable submodular function minimization

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER VISION; GRAPH THEORY; INFORMATION SCIENCE; LEARNING SYSTEMS; SIGNAL PROCESSING;

EID: 84937950158     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (45)

References (38)
  • 2
    • 84889843868 scopus 로고    scopus 로고
    • Learning with submodular functions: A convex optimization perspective
    • F. Bach. Learning with submodular functions: A convex optimization perspective. Foundations and Trends in Machine Learning, 6(2-3):145-373, 2013.
    • (2013) Foundations and Trends in Machine Learning , vol.6 , Issue.2-3 , pp. 145-373
    • Bach, F.1
  • 3
    • 0001448913 scopus 로고
    • On the convergence of von neumann's alternating projection algorithm for two sets
    • H. H. Bauschke and J. M. Borwein. On the convergence of von Neumann's alternating projection algorithm for two sets. Set-Valued Analysis, 1(2):185-212, 1993.
    • (1993) Set-Valued Analysis , vol.1 , Issue.2 , pp. 185-212
    • Bauschke, H.H.1    Borwein, J.M.2
  • 4
    • 0037976260 scopus 로고
    • Dykstra's alternating projection algorithm for two sets
    • H. H. Bauschke and J. M. Borwein. Dykstra's alternating projection algorithm for two sets. Journal of Approximation Theory, 79(3):418-443, 1994.
    • (1994) Journal of Approximation Theory , vol.79 , Issue.3 , pp. 418-443
    • Bauschke, H.H.1    Borwein, J.M.2
  • 5
    • 0030246542 scopus 로고    scopus 로고
    • On projection algorithms for solving convex feasibility problems
    • H. H. Bauschke and J. M. Borwein. On projection algorithms for solving convex feasibility problems. SIAM Review, 38(3):367-426, 1996.
    • (1996) SIAM Review , vol.38 , Issue.3 , pp. 367-426
    • Bauschke, H.H.1    Borwein, J.M.2
  • 6
    • 84903726362 scopus 로고    scopus 로고
    • The rate of linear convergence of the douglas-rachford algorithm for subspaces is the cosine of the friedrichs angle
    • H. H. Bauschke, J. B. Cruz, T. T. Nghia, H. M. Phan, and X. Wang. The rate of linear convergence of the Douglas-Rachford algorithm for subspaces is the cosine of the Friedrichs angle. Journal of Approximation Theory, 185:63-79, 2014.
    • (2014) Journal of Approximation Theory , vol.185 , pp. 63-79
    • Bauschke, H.H.1    Cruz, J.B.2    Nghia, T.T.3    Phan, H.M.4    Wang, X.5
  • 7
    • 84892868336 scopus 로고    scopus 로고
    • On the convergence of block coordinate descent type methods
    • A. Beck and L. Tetruashvili. On the convergence of block coordinate descent type methods. SIAM Journal on Optimization, 23(4):2037-2060, 2013.
    • (2013) SIAM Journal on Optimization , vol.23 , Issue.4 , pp. 2037-2060
    • Beck, A.1    Tetruashvili, L.2
  • 8
    • 0000880309 scopus 로고
    • On the identification of active constraints
    • J. V. Burke and J. J. Moré. On the identification of active constraints. SIAM Journal on Numerical Analysis, 25(5):1197-1211, 1988.
    • (1988) SIAM Journal on Numerical Analysis , vol.25 , Issue.5 , pp. 1197-1211
    • Burke, J.V.1    Moré, J.J.2
  • 12
    • 0002969298 scopus 로고
    • The rate of convergence of dykstra's cyclic projections algorithm: The polyhedral case
    • F. Deutsch and H. Hundal. The rate of convergence of Dykstra's cyclic projections algorithm: The polyhedral case. Numerical Functional Analysis and Optimization, 15(5-6):537-565, 1994.
    • (1994) Numerical Functional Analysis and Optimization , vol.15 , Issue.5-6 , pp. 537-565
    • Deutsch, F.1    Hundal, H.2
  • 13
    • 33748169660 scopus 로고    scopus 로고
    • The rate of convergence for the cyclic projections algorithm I: Angles between convex sets
    • F. Deutsch and H. Hundal. The rate of convergence for the cyclic projections algorithm I: angles between convex sets. Journal of Approximation Theory, 142(1):36-55, 2006.
    • (2006) Journal of Approximation Theory , vol.142 , Issue.1 , pp. 36-55
    • Deutsch, F.1    Hundal, H.2
  • 15
    • 3643114014 scopus 로고
    • chapter Submodular Functions, Matroids and Certain Polyhedra Gordon and Breach
    • J. Edmonds. Combinatorial Structures and Their Applications, chapter Submodular Functions, Matroids and Certain Polyhedra, pages 69-87. Gordon and Breach, 1970.
    • (1970) Combinatorial Structures and their Applications , pp. 69-87
    • Edmonds, J.1
  • 17
    • 79951736547 scopus 로고    scopus 로고
    • A submodular function minimization algorithm based on the minimum-norm base
    • S. Fujishige and S. Isotani. A submodular function minimization algorithm based on the minimum-norm base. Pacific Journal of Optimization, 7:3-17, 2011.
    • (2011) Pacific Journal of Optimization , vol.7 , pp. 3-17
    • Fujishige, S.1    Isotani, S.2
  • 19
    • 51249185617 scopus 로고
    • The ellipsoid method and its consequences in combinatorial optimization
    • M. Grötschel, L. Lovász, and A. Schrijver. The ellipsoid method and its consequences in combinatorial optimization. Combinatorica, 1(2):169-197, 1981.
    • (1981) Combinatorica , vol.1 , Issue.2 , pp. 169-197
    • Grötschel, M.1    Lovász, L.2    Schrijver, A.3
  • 21
    • 0002477272 scopus 로고
    • The product of projection operators
    • I. Halperin. The product of projection operators. Acta Sci. Math. (Szeged), 23:96-99, 1962.
    • (1962) Acta Sci. Math. (Szeged) , vol.23 , pp. 96-99
    • Halperin, I.1
  • 23
    • 0141534137 scopus 로고    scopus 로고
    • A faster scaling algorithm for minimizing submodular functions
    • S. Iwata. A faster scaling algorithm for minimizing submodular functions. SIAM J. on Computing, 32: 833-840, 2003.
    • (2003) SIAM J. on Computing , vol.32 , pp. 833-840
    • Iwata, S.1
  • 26
    • 80052234083 scopus 로고    scopus 로고
    • Proximal methods for hierarchical sparse coding
    • R. Jenatton, J. Mairal, G. Obozinski, and F. Bach. Proximal methods for hierarchical sparse coding. JMLR, page 2297-2334, 2011.
    • (2011) JMLR , pp. 2297-2334
    • Jenatton, R.1    Mairal, J.2    Obozinski, G.3    Bach, F.4
  • 27
    • 0036449633 scopus 로고    scopus 로고
    • Principal angles between subspaces in an A-based scalar product: Algorithms and perturbation estimates
    • A. V. Knyazev and M. E. Argentati. Principal angles between subspaces in an A-based scalar product: algorithms and perturbation estimates. SIAM Journal on Scientific Computing, 23(6):2008-2040, 2002.
    • (2002) SIAM Journal on Scientific Computing , vol.23 , Issue.6 , pp. 2008-2040
    • Knyazev, A.V.1    Argentati, M.E.2
  • 29
    • 84864761190 scopus 로고    scopus 로고
    • Minimizing a sum of submodular functions
    • V. Kolmogorov. Minimizing a sum of submodular functions. Discrete Applied Mathematics, 160(15): 2246-2258, 2012.
    • (2012) Discrete Applied Mathematics , vol.160 , Issue.15 , pp. 2246-2258
    • Kolmogorov, V.1
  • 31
    • 84865756305 scopus 로고    scopus 로고
    • Optimal selection of limited vocabulary speech corpora
    • H. Lin and J. Bilmes. Optimal selection of limited vocabulary speech corpora. In Proc. Interspeech, 2011.
    • (2011) Proc. Interspeech
    • Lin, H.1    Bilmes, J.2
  • 32
    • 33746946442 scopus 로고    scopus 로고
    • chapter Submodular Function Minimization Elsevier
    • S. McCormick. Handbook on Discrete Optimization, chapter Submodular Function Minimization, pages 321-391. Elsevier, 2006.
    • (2006) Handbook on Discrete Optimization , pp. 321-391
    • McCormick, S.1
  • 33
    • 84860635284 scopus 로고    scopus 로고
    • Local search for balanced submodular clusterings
    • M. Narasimhan and J. Bilmes. Local search for balanced submodular clusterings. In IJCAI, pages 981-986, 2007.
    • (2007) IJCAI , pp. 981-986
    • Narasimhan, M.1    Bilmes, J.2
  • 34
    • 58149485960 scopus 로고    scopus 로고
    • A faster strongly polynomial time algorithm for submodular function minimization
    • J. Orlin. A faster strongly polynomial time algorithm for submodular function minimization. Math. Programming, 118:237-251, 2009.
    • (2009) Math. Programming , vol.118 , pp. 237-251
    • Orlin, J.1
  • 36
    • 0031285675 scopus 로고    scopus 로고
    • Alternating projection-proximal methods for convex programming and variational inequalities
    • P. Tseng. Alternating projection-proximal methods for convex programming and variational inequalities. SIAM Journal on Optimization, 7(4):951-965, 1997.
    • (1997) SIAM Journal on Optimization , vol.7 , Issue.4 , pp. 951-965
    • Tseng, P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.