Random matrix

Results: 401



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51Feature Selection and Pose Estimation From Known Planar Objects Using Monocular Vision Shengdong Xu1 and Ming Liu2 1  2

Feature Selection and Pose Estimation From Known Planar Objects Using Monocular Vision Shengdong Xu1 and Ming Liu2 1 2

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Source URL: www.ee.ust.hk

Language: English - Date: 2014-01-06 09:48:04
52AN ASYMPTOTIC FORMULA FOR THE NUMBER OF NON-NEGATIVE INTEGER MATRICES WITH PRESCRIBED ROW AND COLUMN SUMS Alexander Barvinok and J.A. Hartigan March 2011

AN ASYMPTOTIC FORMULA FOR THE NUMBER OF NON-NEGATIVE INTEGER MATRICES WITH PRESCRIBED ROW AND COLUMN SUMS Alexander Barvinok and J.A. Hartigan March 2011

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Source URL: www.math.lsa.umich.edu

Language: English - Date: 2011-03-10 19:58:36
53BACK S HIFT :  Learning causal cyclic graphs from unknown shift interventions  Dominik Rothenh¨ausler⇤

BACK S HIFT : Learning causal cyclic graphs from unknown shift interventions Dominik Rothenh¨ausler⇤

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Source URL: papers.nips.cc

Language: English - Date: 2015-12-18 15:54:52
54RandNLA: Randomization in Numerical Linear Algebra: Theory and Practice Petros Drineas RPI

RandNLA: Randomization in Numerical Linear Algebra: Theory and Practice Petros Drineas RPI

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Source URL: www.drineas.org

Language: English - Date: 2015-10-26 09:53:58
55THE NUMBER OF GRAPHS AND A RANDOM GRAPH WITH A GIVEN DEGREE SEQUENCE Alexander Barvinok and J.A. Hartigan November 2011 Abstract. We consider the set of all graphs on n labeled vertices with prescribed

THE NUMBER OF GRAPHS AND A RANDOM GRAPH WITH A GIVEN DEGREE SEQUENCE Alexander Barvinok and J.A. Hartigan November 2011 Abstract. We consider the set of all graphs on n labeled vertices with prescribed

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Source URL: www.math.lsa.umich.edu

Language: English - Date: 2011-11-22 11:29:45
56ENUMERATING CONTINGENCY TABLES VIA RANDOM PERMANENTS Alexander Barvinok March 2006 Abstract. Given m positive integers R = (ri ), n positive integers C = (cj ) such

ENUMERATING CONTINGENCY TABLES VIA RANDOM PERMANENTS Alexander Barvinok March 2006 Abstract. Given m positive integers R = (ri ), n positive integers C = (cj ) such

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Source URL: www.math.lsa.umich.edu

Language: English - Date: 2006-03-07 12:57:11
57WHAT DOES A RANDOM CONTINGENCY TABLE LOOK LIKE? Alexander Barvinok November 2009 Abstract. Let R = (r1 , . . . , rm ) and C = (c1 , . . . , cn ) be positive integer vectors

WHAT DOES A RANDOM CONTINGENCY TABLE LOOK LIKE? Alexander Barvinok November 2009 Abstract. Let R = (r1 , . . . , rm ) and C = (c1 , . . . , cn ) be positive integer vectors

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Source URL: www.math.lsa.umich.edu

Language: English - Date: 2009-11-25 09:10:05
58Combinatorics and geometry of tensor models, generalization of random matrix models ˘ ADRIAN TANASA DFT in collaboration with:

Combinatorics and geometry of tensor models, generalization of random matrix models ˘ ADRIAN TANASA DFT in collaboration with:

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Source URL: events.theory.nipne.ro

Language: English - Date: 2014-07-26 19:05:04
    59ON THE NUMBER OF MATRICES AND A RANDOM MATRIX WITH PRESCRIBED ROW AND COLUMN SUMS AND 0-1 ENTRIES Alexander Barvinok November 2009

    ON THE NUMBER OF MATRICES AND A RANDOM MATRIX WITH PRESCRIBED ROW AND COLUMN SUMS AND 0-1 ENTRIES Alexander Barvinok November 2009

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    Source URL: www.math.lsa.umich.edu

    Language: English - Date: 2009-11-25 09:07:37
    60Stochastic approximation of score functions for Gaussian processes

    Stochastic approximation of score functions for Gaussian processes

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    Source URL: arxiv.org

    Language: English - Date: 2013-12-10 20:17:39