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Dąbrowski
Results: 94

#	Item
71	Mitigating Global Failure Regimes in Large Distributed Systems (Ongoing Research) C. Dabrowski, J. Filliben, K. Mills, S. Ressler and B. Rust from NIST No effective methods exist to predict failure regimes in large distr Add to Reading List Source URL: www.nist.gov Language: English - Date: 2012-09-05 11:18:57 Markov chain Machine learning Probability and statistics Simulation Forward–backward algorithm Perceptron Markov models Statistics Markov processes
72	Predicting the Unpredictable in Complex Information Systems Kevin Mills NIST Joint work with Chris Dabrowski, Jim Filliben and Sandy Ressler of NIST and Yan Wan of University of North Texas Add to Reading List Source URL: www.nist.gov Language: English - Date: 2014-01-28 09:31:30 Computing Lattice models Network performance Teletraffic Network congestion Percolation theory Percolation threshold Transmission Control Protocol Network simulation Physics Critical phenomena Phase transitions
73	Practical Challenges when Implementing a Distributed Population of Cloud-Computing Simulators Controlled by a Genetic Algorithm K. Mills, C. Dabrowski & D. Santay National Institute of Standards & Technology Gaithersburg Add to Reading List Source URL: www.nist.gov Language: English - Date: 2013-04-02 10:45:35 Parallel computing Electronic design automation Cybernetics Genetic algorithm Mathematical optimization Computer cluster Simulation Mass spectrometry software Logic simulation Computing Electronic engineering Digital electronics
74	Efficient Sensitivity Analysis Method for Large Cloud Simulations Kevin Mills, James Filliben and Chris Dabrowski from NIST Proceedings of IEEE Cloud 2011, Washington D.C., July 4-9, 2011 We developed an objective method Add to Reading List Source URL: www.nist.gov Language: English - Date: 2011-11-07 10:24:37 Markov processes Markov chain Computer cluster Koala Mammals of Australia Computing Markov models
75	Mitigating Global Failure Regimes in Large Distributed Systems (Ongoing Research) C. Dabrowski, J. Filliben, K. Mills, S. Ressler and B. Rust from NIST No effective methods exist to predict failure regimes in large distr Add to Reading List Source URL: www.nist.gov Language: English - Date: 2012-06-11 13:51:25 Markov chain Machine learning Probability and statistics Simulation Forward–backward algorithm Perceptron Markov models Statistics Markov processes
76	Innovations in Measurement Science USING MARKOV CHAIN AND GRAPH THEORY CONCEPTS TO ANALYZE BEHAVIOR IN COMPLEX DISTRIBUTED SYSTEMS Christopher Dabrowski Add to Reading List Source URL: www.nist.gov Language: English - Date: 2011-09-30 14:10:24 Markov chain Simulation MEMO Model Environmental science Probability and statistics Markov models Markov processes Statistics
77	Predicting Global Failure Regimes in Complex Information Networks Chris Dabrowski, Jim Filliben and Kevin Mills July 12, 2012 SFI Workshop on Measurement of Complex Networks A2a Add to Reading List Source URL: www.nist.gov Language: English - Date: 2012-07-11 16:53:37 Markov models Markov chain Parameter Sensitivity analysis Genetic algorithm Reliability engineering Statistics Mathematics Science
78	Dabrowski, Filliben and Mills NIST March 2012 Add to Reading List Source URL: www.nist.gov Language: English - Date: 2012-06-11 13:55:53 Forecasting Genetic algorithm Simulation Statistics Mathematical sciences Markov chain
79	Combining Genetic Algorithms & Simulation to Search for Failure Scenarios in System Models Kevin Mills National Institute of Standards & Technology (NIST) Joint work with NIST colleagues: Chris Dabrowski Jim Filliben Add to Reading List Source URL: www.nist.gov Language: English - Date: 2014-02-25 10:12:49 Science Genetic algorithms Mathematical optimization Applied mathematics Parameter Selection Control theory Cybernetics Mathematics Search algorithms
80	Combining Genetic Algorithms & Simulation to Search for Failure Scenarios in System Models Project Team: Kevin Mills, computer scientist – [removed] Chris Dabrowski, computer scientist – [removed] Jim Add to Reading List Source URL: www.nist.gov Language: English - Date: 2013-10-24 11:16:18 Cybernetics Mathematical optimization Science Selection Statistics Parameter Statistic Statistical theory Mathematics Genetic algorithms

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