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» A Model for Large Scale Self-Stabilization
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ICML
2008
IEEE
14 years 9 months ago
Empirical Bernstein stopping
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...
Csaba Szepesvári, Jean-Yves Audibert, Volod...
ICML
2005
IEEE
14 years 9 months ago
Fast condensed nearest neighbor rule
We present a novel algorithm for computing a training set consistent subset for the nearest neighbor decision rule. The algorithm, called FCNN rule, has some desirable properties....
Fabrizio Angiulli
ICIAP
2007
ACM
14 years 9 months ago
A Framework for False Positive Suppression in Video Segmentation
Object detection in video surveillance is typically done through background subtraction or temporal differencing. While these techniques perform very well under scenes where there...
Min Han Tun, Geoff A. W. West, Tele Tan
IROS
2009
IEEE
168views Robotics» more  IROS 2009»
14 years 3 months ago
DASH: A dynamic 16g hexapedal robot
—DASH is a small, lightweight, power autonomous robot capable of running at speeds up to 15 body lengths per second (see video). Drawing inspiration from biomechanics, DASH has a...
Paul Birkmeyer, Kevin Peterson, Ronald S. Fearing
WOWMOM
2009
ACM
143views Multimedia» more  WOWMOM 2009»
14 years 3 months ago
Improving partial cover of Random Walks in large-scale Wireless Sensor Networks
Random Walks (RWs) have been considered for information dissemination in large scale, dynamic and unstructured environments, as they are scalable, robust to topology changes and d...
Leonidas Tzevelekas, Ioannis Stavrakakis