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STOC
2003
ACM
154views Algorithms» more  STOC 2003»
14 years 10 months ago
Boosting in the presence of noise
Boosting algorithms are procedures that "boost" low-accuracy weak learning algorithms to achieve arbitrarily high accuracy. Over the past decade boosting has been widely...
Adam Kalai, Rocco A. Servedio
VLDB
2006
ACM
190views Database» more  VLDB 2006»
14 years 10 months ago
Online summarization of dynamic time series data
Managing large-scale time series databases has attracted significant attention in the database community recently. Related fundamental problems such as dimensionality reduction, tr...
Ümit Y. Ogras, Hakan Ferhatosmanoglu
SDM
2009
SIAM
193views Data Mining» more  SDM 2009»
14 years 7 months ago
Agglomerative Mean-Shift Clustering via Query Set Compression.
Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets...
Xiaotong Yuan, Bao-Gang Hu, Ran He
FOCS
2009
IEEE
14 years 5 months ago
KKL, Kruskal-Katona, and Monotone Nets
We generalize the Kahn-Kalai-Linial (KKL) Theorem to random walks on Cayley and Schreier graphs, making progress on an open problem of Hoory, Linial, and Wigderson. In our general...
Ryan O'Donnell, Karl Wimmer
IROS
2009
IEEE
132views Robotics» more  IROS 2009»
14 years 5 months ago
Segregation in swarms of mobile robots based on the Brazil nut effect
— We study a simple algorithm inspired by the Brazil nut effect for achieving segregation in a swarm of mobile robots. The algorithm lets each robot mimic a particle of a certain...
Roderich Groß, Stéphane Magnenat, Fra...