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» Accelerating Large Data Analysis by Exploiting Regularities
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94
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NIPS
2001
15 years 1 months ago
Partially labeled classification with Markov random walks
To classify a large number of unlabeled examples we combine a limited number of labeled examples with a Markov random walk representation over the unlabeled examples. The random w...
Martin Szummer, Tommi Jaakkola
89
Voted
LISA
1993
15 years 1 months ago
Forecasting Disk Resource Requirements for a Usenet Server
Three years ago the Stanford Linear Accelerator Center (SLAC) decided to embrace netnews as a site-wide, multi-platform communications tool for the laboratory’s diverse user com...
Karl L. Swartz
SIGMOD
2008
ACM
131views Database» more  SIGMOD 2008»
15 years 11 months ago
Domain adaptation of information extraction models
Domain adaptation refers to the process of adapting an extraction model trained in one domain to another related domain with only unlabeled data. We present a brief survey of exis...
Rahul Gupta, Sunita Sarawagi
126
Voted
ESI
2010
119views more  ESI 2010»
14 years 6 months ago
A roadmap for a dedicated Earth Science Grid platform
Due to its intensive data processing and highly distributed organization, the multidisciplinary Earth Science applications community is uniquely positioned for the uptake and explo...
Roberto Cossu, Monique Petitdidier, Julian Linford...
96
Voted
SDM
2004
SIAM
211views Data Mining» more  SDM 2004»
15 years 1 months ago
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...