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EUROPAR
2009
Springer
15 years 11 months ago
Capturing and Visualizing Event Flow Graphs of MPI Applications
A high-level understanding of how an application executes and which performance characteristics it exhibits is essential in many areas of high performance computing, such as applic...
Karl Fürlinger, David Skinner
JMLR
2006
113views more  JMLR 2006»
15 years 6 months ago
Learning the Structure of Linear Latent Variable Models
We describe anytime search procedures that (1) find disjoint subsets of recorded variables for which the members of each subset are d-separated by a single common unrecorded cause...
Ricardo Silva, Richard Scheines, Clark Glymour, Pe...
IJAR
2010
152views more  IJAR 2010»
15 years 5 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
JMLR
2010
128views more  JMLR 2010»
15 years 1 months ago
Learning Causal Structure from Overlapping Variable Sets
We present an algorithm name cSAT+ for learning the causal structure in a domain from datasets measuring different variable sets. The algorithm outputs a graph with edges correspo...
Sofia Triantafilou, Ioannis Tsamardinos, Ioannis G...
CORR
2011
Springer
199views Education» more  CORR 2011»
15 years 1 months ago
Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining
Scaling up the sparse matrix-vector multiplication kernel on modern Graphics Processing Units (GPU) has been at the heart of numerous studies in both academia and industry. In thi...
Xintian Yang, Srinivasan Parthasarathy, Ponnuswamy...