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139
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KDD
2009
ACM
227views Data Mining» more  KDD 2009»
16 years 4 months ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
123
Voted
SLIP
2005
ACM
15 years 9 months ago
Congestion prediction in early stages
Routability optimization has become a major concern in the physical design cycle of VLSI circuits. Due to the recent advances in VLSI technology, interconnect has become a dominan...
Chiu-Wing Sham, Evangeline F. Y. Young
130
Voted
BMCBI
2010
106views more  BMCBI 2010»
15 years 3 months ago
TumorBoost: Normalization of allele-specific tumor copy numbers from a single pair of tumor-normal genotyping microarrays
Background: High-throughput genotyping microarrays assess both total DNA copy number and allelic composition, which makes them a tool of choice for copy number studies in cancer, ...
Henrik Bengtsson, Pierre Neuvial, Terence P. Speed
128
Voted
BMCBI
2008
144views more  BMCBI 2008»
15 years 3 months ago
Local conservation scores without a priori assumptions on neutral substitution rates
Background: Comparative genomics aims to detect signals of evolutionary conservation as an indicator of functional constraint. Surprisingly, results of the ENCODE project revealed...
Janis Dingel, Pavol Hanus, Niccolò Leonardi...
297
Voted

Book
5396views
17 years 2 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li