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» Predicting relative performance of classifiers from samples
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KDD
2010
ACM
247views Data Mining» more  KDD 2010»
13 years 9 months ago
Active learning for biomedical citation screening
Active learning (AL) is an increasingly popular strategy for mitigating the amount of labeled data required to train classifiers, thereby reducing annotator effort. We describe ...
Byron C. Wallace, Kevin Small, Carla E. Brodley, T...
BMCBI
2007
120views more  BMCBI 2007»
13 years 7 months ago
Non-coding sequence retrieval system for comparative genomic analysis of gene regulatory elements
Background: Completion of the human genome sequence along with other species allows for greater understanding of the biochemical mechanisms and processes that govern healthy as we...
Sung Tae Doh, Yunyu Zhang, Matthew H. Temple, Li C...
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
14 years 8 months ago
Locality sensitive hash functions based on concomitant rank order statistics
: Locality Sensitive Hash functions are invaluable tools for approximate near neighbor problems in high dimensional spaces. In this work, we are focused on LSH schemes where the si...
Kave Eshghi, Shyamsundar Rajaram
CHI
2010
ACM
14 years 2 months ago
Mobile taskflow in context: a screenshot study of smartphone usage
The impact of interruptions on workflow and productivity has been extensively studied in the PC domain, but while fragmented user attention is recognized as an inherent aspect of ...
Amy K. Karlson, Shamsi T. Iqbal, Brian Meyers, Gon...
ACIVS
2006
Springer
14 years 1 months ago
Visibility of Point Clouds and Mapping of Unknown Environments
Abstract. We present an algorithm for interpolating the visible portions of a point cloud that are sampled from opaque objects in the environment. Our algorithm projects point clou...
Yanina Landa, Richard Tsai, Li-Tien Cheng