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» Predicting graph reading performance: a cognitive approach
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SDM
2010
SIAM
182views Data Mining» more  SDM 2010»
15 years 7 months ago
HCDF: A Hybrid Community Discovery Framework
We introduce a novel Bayesian framework for hybrid community discovery in graphs. Our framework, HCDF (short for Hybrid Community Discovery Framework), can effectively incorporate...
Keith Henderson, Tina Eliassi-Rad, Spiros Papadimi...
ICPP
1999
IEEE
15 years 10 months ago
SLC: Symbolic Scheduling for Executing Parameterized Task Graphs on Multiprocessors
Task graph scheduling has been found effective in performance prediction and optimization of parallel applications. A number of static scheduling algorithms have been proposed for...
Michel Cosnard, Emmanuel Jeannot, Tao Yang
FLAIRS
2010
15 years 8 months ago
Meta-Prediction for Collective Classification
When data instances are inter-related, as are nodes in a social network or hyperlink graph, algorithms for collective classification (CC) can significantly improve accuracy. Recen...
Luke McDowell, Kalyan Moy Gupta, David W. Aha
CCGRID
2009
IEEE
16 years 23 days ago
Performance under Failures of DAG-based Parallel Computing
— As the scale and complexity of parallel systems continue to grow, failures become more and more an inevitable fact for solving large-scale applications. In this research, we pr...
Hui Jin, Xian-He Sun, Ziming Zheng, Zhiling Lan, B...
ICML
2009
IEEE
16 years 6 months ago
Graph construction and b-matching for semi-supervised learning
Graph based semi-supervised learning (SSL) methods play an increasingly important role in practical machine learning systems. A crucial step in graph based SSL methods is the conv...
Tony Jebara, Jun Wang, Shih-Fu Chang