Yolanda Gil
TitleCited byYear
Beyond Regression:" New Tools for Prediction and Analysis in the Behavioral Sciences
P Werbos
Ph. D. dissertation, Harvard University, 1974
Solution of incorrectly formaulated problems and the regularization method
AN Tikhonov
Dokl. Akad. Nauk. 151, 1035-1038, 1963
Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
SM Weiss, CA Kulikowski
Morgan Kaufmann Publishers Inc., 1991
Tracking and data association
Y Bar-Shalom
Academic Press Professional, Inc., 1987
Theoretical foundations of the potential function method in pattern recognition learning
MA Aizerman
Automation and remote control 25, 821-837, 1964
Pegasus: A framework for mapping complex scientific workflows onto distributed systems
E Deelman, G Singh, MH Su, J Blythe, Y Gil, C Kesselman, G Mehta, ...
Scientific Programming 13 (3), 219-237, 2005
Interpolated estimation of Markov source parameters from sparse data
F Jelinek
Proc. Workshop on Pattern Recognition in Practice, 1980, 1980
The open provenance model core specification (v1. 1)
L Moreau, B Clifford, J Freire, J Futrelle, Y Gil, P Groth, N Kwasnikowska, ...
Future generation computer systems 27 (6), 743-756, 2011
A survey of trust in computer science and the semantic web
D Artz, Y Gil
Web Semantics: Science, Services and Agents on the World Wide Web 5 (2), 58-71, 2007
Examining the challenges of scientific workflows
Y Gil, E Deelman, M Ellisman, T Fahringer, G Fox, D Gannon, C Goble, ...
Computer 40 (12), 24-32, 2007
Pegasus: Mapping scientific workflows onto the grid
E Deelman, J Blythe, Y Gil, C Kesselman, G Mehta, S Patil, MH Su, K Vahi, ...
European Across Grids Conference, 11-20, 2004
Mapping abstract complex workflows onto grid environments
E Deelman, J Blythe, Y Gil, C Kesselman, G Mehta, K Vahi, K Blackburn, ...
Journal of Grid Computing 1 (1), 25-39, 2003
Naming, necessity, and natural kinds
SP Schwartz
Task scheduling strategies for workflow-based applications in grids
J Blythe, S Jain, E Deelman, Y Gil, K Vahi, A Mandal, K Kennedy
CCGrid 2005. IEEE International Symposium on Cluster Computing and the Grid …, 2005
Explanation-based learning: A problem solving perspective
S Minton, JG Carbonell, CA Knoblock, DR Kuokka, O Etzioni, Y Gil
Artificial Intelligence 40 (1-3), 63-118, 1989
Readings in medical artificial intelligence: the first decade
WJ Clancey, EH Shortliffe
Addison-Wesley Longman Publishing Co., Inc., 1984
Prodigy: An integrated architecture for planning and learning
JG Carbonell, CA Knoblock, S Minton
Architectures for intelligence, 255-292, 2014
The first provenance challenge
L Moreau, B Ludäscher, I Altintas, RS Barga, S Bowers, S Callahan, ...
Concurrency and computation: practice and experience 20 (5), 409-418, 2008
Prov-dm: The prov data model
L Moreau, P Missier, K Belhajjame, R B’Far, J Cheney, S Coppens, ...
Retrieved July 30 (2013), W3C, 2013
Towards content trust of web resources
Y Gil, D Artz
Web Semantics: Science, Services and Agents on the World Wide Web 5 (4), 227-239, 2007
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Articles 1–20