Sciweavers

1550 search results - page 85 / 310
» Benchmarking for Graph Transformation
Sort
View
116
Voted
ICML
2009
IEEE
16 years 4 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
AIPS
2008
15 years 5 months ago
Unifying the Causal Graph and Additive Heuristics
Many current heuristics for domain-independent planning, such as Bonet and Geffner's additive heuristic and Hoffmann and Nebel's FF heuristic, are based on delete relaxa...
Malte Helmert, Hector Geffner
CIKM
2008
Springer
15 years 5 months ago
Structure feature selection for graph classification
With the development of highly efficient graph data collection technology in many application fields, classification of graph data emerges as an important topic in the data mining...
Hongliang Fei, Jun Huan
123
Voted
PVLDB
2010
151views more  PVLDB 2010»
15 years 1 months ago
Scalable Discovery of Best Clusters on Large Graphs
The identification of clusters, well-connected components in a graph, is useful in many applications from biological function prediction to social community detection. However, ...
Kathy Macropol, Ambuj K. Singh
DSD
2007
IEEE
120views Hardware» more  DSD 2007»
15 years 9 months ago
Latency Minimization for Synchronous Data Flow Graphs
Synchronous Data Flow Graphs (SDFGs) are a very useful means for modeling and analyzing streaming applications. Some performance indicators, such as throughput, have been studied b...
Amir Hossein Ghamarian, Sander Stuijk, Twan Basten...