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BMCBI
2006
165views more  BMCBI 2006»
15 years 2 months ago
Improved variance estimation of classification performance via reduction of bias caused by small sample size
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...
Ulrika Wickenberg-Bolin, Hanna Göransson, M&a...
155
Voted
TIT
2008
141views more  TIT 2008»
15 years 2 months ago
Dimensionality Reduction for Distributed Estimation in the Infinite Dimensional Regime
Distributed estimation of an unknown signal is a common task in sensor networks. The scenario usually envisioned consists of several nodes, each making an observation correlated wi...
Olivier Roy, Martin Vetterli
158
Voted
JCSC
2002
129views more  JCSC 2002»
15 years 2 months ago
Leakage Current Reduction in VLSI Systems
There is a growing need to analyze and optimize the stand-by component of power in digital circuits designed for portable and battery-powered applications. Since these circuits re...
David Blaauw, Steven M. Martin, Trevor N. Mudge, K...
CLEF
2006
Springer
15 years 6 months ago
Vocabulary Reduction and Text Enrichment at WebCLEF
Nowadays, cross-lingual Information Retrieval (IR) is one of the greatest challenges to deal with. Besides, one of the most important issues in IR consists in the corpus vocabular...
Franco Rojas López, Héctor Jim&eacut...
124
Voted
AAAI
2010
15 years 4 months ago
Multi-Instance Dimensionality Reduction
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
Yu-Yin Sun, Michael K. Ng, Zhi-Hua Zhou