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» Identifying graphs from noisy and incomplete data
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INFOCOM
2009
IEEE
14 years 2 months ago
Distributed Opportunistic Scheduling With Two-Level Channel Probing
Distributed opportunistic scheduling (DOS) is studied for wireless ad-hoc networks in which many links contend for the channel using random access before data transmissions. Simpl...
P. S. Chandrashekhar Thejaswi, Junshan Zhang, Man-...
ICDM
2006
IEEE
166views Data Mining» more  ICDM 2006»
14 years 1 months ago
Mining Generalized Graph Patterns Based on User Examples
There has been a lot of recent interest in mining patterns from graphs. Often, the exact structure of the patterns of interest is not known. This happens, for example, when molecu...
Pavel Dmitriev, Carl Lagoze
CHI
2008
ACM
14 years 8 months ago
Increasing the utility of quantitative empirical studies for meta-analysis
Despite the long history and consistent use of quantitative empirical methods to evaluate information visualization techniques and systems, our understanding of interface use rema...
Heidi Lam, Tamara Munzner
USENIX
2007
13 years 10 months ago
Using Provenance to Aid in Personal File Search
As the scope of personal data grows, it becomes increasingly difficult to find what we need when we need it. Desktop search tools provide a potential answer, but most existing too...
Sam Shah, Craig A. N. Soules, Gregory R. Ganger, B...
AUSAI
2008
Springer
13 years 9 months ago
Learning to Find Relevant Biological Articles without Negative Training Examples
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Keith Noto, Milton H. Saier Jr., Charles Elkan