Markov number

Results: 88



#Item
11Partition Models As A Framework For Multiplicative Models For Categorical Data Anna Klimova, Department Of Statistics, University Of Washington Joint Work With Tamas Rudas, Adrian Dobra June 4, 2009  {n0:χ2(n0)≥χ2(n)

Partition Models As A Framework For Multiplicative Models For Categorical Data Anna Klimova, Department Of Statistics, University Of Washington Joint Work With Tamas Rudas, Adrian Dobra June 4, 2009 {n0:χ2(n0)≥χ2(n)

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Source URL: www.csss.washington.edu

Language: English - Date: 2009-07-06 14:04:14
120.1  factor.mix: Mixed Data Factor Analysis Mixed data factor analysis takes both continuous and ordinal dependent variables and estimates a model for a given number of latent factors. The model is estimated using a Mark

0.1 factor.mix: Mixed Data Factor Analysis Mixed data factor analysis takes both continuous and ordinal dependent variables and estimates a model for a given number of latent factors. The model is estimated using a Mark

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Source URL: perso.md2t.eu

Language: English - Date: 2011-03-08 17:52:46
13Graduate student ACM Student Member Number: Advisor: Prof. Xin Li Member of ACM SIGDA: yes

Graduate student ACM Student Member Number: Advisor: Prof. Xin Li Member of ACM SIGDA: yes

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Source URL: src.acm.org

Language: English - Date: 2015-05-18 11:00:35
14Buffer Occupancy and Delay Asymptotics in Multi-buffered Systems with Generalized Processor Sharing Handling a Large Number of Independent Traffic Streams∗ Constantinos Kotopoulos Department of Mathematics

Buffer Occupancy and Delay Asymptotics in Multi-buffered Systems with Generalized Processor Sharing Handling a Large Number of Independent Traffic Streams∗ Constantinos Kotopoulos Department of Mathematics

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Source URL: ece.uwaterloo.ca

Language: English - Date: 2002-03-06 11:35:47
15Department of Mathematics Texas A&M University 3368 TAMU College Station, TXF

Department of Mathematics Texas A&M University 3368 TAMU College Station, TXF

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Source URL: see-math.math.tamu.edu

Language: English - Date: 2015-02-14 23:22:02
16Globs in the Primordial Soup The Emergence of Connected Crowds in Mobile Wireless Networks Simon Heimlicher Kavé Salamatian

Globs in the Primordial Soup The Emergence of Connected Crowds in Mobile Wireless Networks Simon Heimlicher Kavé Salamatian

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Source URL: www.sigmobile.org

Language: English
17Time-Markovian Representation of Spatio-Temporal Gaussian Processes (with Applications) Simo S¨arkk¨a Department of Biomedical Engineering and Computational Science (BECS) Aalto University, Espoo, Finland

Time-Markovian Representation of Spatio-Temporal Gaussian Processes (with Applications) Simo S¨arkk¨a Department of Biomedical Engineering and Computational Science (BECS) Aalto University, Espoo, Finland

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Source URL: inverse-problems.org

Language: English - Date: 2013-09-02 06:15:32
18CCCG 2007, Ottawa, Ontario, August 20–22, 2007  Improved Upper Bounds on the Reflexivity of Point Sets Eyal Ackerman∗  Oswin Aichholzer†

CCCG 2007, Ottawa, Ontario, August 20–22, 2007 Improved Upper Bounds on the Reflexivity of Point Sets Eyal Ackerman∗ Oswin Aichholzer†

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Source URL: cccg.ca

Language: English - Date: 2008-10-28 21:29:45
19Covering Number for Efficient Heuristic-Based POMDP Planning  Zongzhang Zhang ZHANGZZ @ COMP. NUS . EDU . SG David Hsu DYHSU @ COMP. NUS . EDU . SG

Covering Number for Efficient Heuristic-Based POMDP Planning Zongzhang Zhang ZHANGZZ @ COMP. NUS . EDU . SG David Hsu DYHSU @ COMP. NUS . EDU . SG

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Source URL: www.comp.nus.edu.sg

Language: English - Date: 2014-07-04 06:57:08
20Inferring the Number of Component Spectra in Multiplexed SERRS M. Zhong*, M. Girolami*, K. Faulds**, & D.Graham** * Inference Group, Department of Computing Science, University of Glasgow, http://www.dcs.gla.ac.uk/infere

Inferring the Number of Component Spectra in Multiplexed SERRS M. Zhong*, M. Girolami*, K. Faulds**, & D.Graham** * Inference Group, Department of Computing Science, University of Glasgow, http://www.dcs.gla.ac.uk/infere

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Source URL: www.dcs.gla.ac.uk

Language: English - Date: 2009-01-27 07:16:33