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DATAMINE
2006
127views more  DATAMINE 2006»
15 years 6 months ago
Computing LTS Regression for Large Data Sets
Least trimmed squares (LTS) regression is based on the subset of h cases (out of n) whose least squares t possesses the smallest sum of squared residuals. The coverage h may be se...
Peter Rousseeuw, Katrien van Driessen
179
Voted
IJCV
2006
100views more  IJCV 2006»
15 years 6 months ago
A General Framework for Combining Visual Trackers - The "Black Boxes" Approach
Abstract. Over the past few years researchers have been investigating the enhancement of visual tracking performance by devising trackers that simultaneously make use of several di...
Ido Leichter, Michael Lindenbaum, Ehud Rivlin
KES
2006
Springer
15 years 6 months ago
Robust Positioning a Mobile Robot with Active Beacon Sensors
With the development of service robots and with the emerging concept of the ubiquitous world, localization of a mobile robot has become a popular issue. Even though several localiz...
JaeMu Yun, SungBu Kim, JangMyung Lee
197
Voted
NN
2006
Springer
232views Neural Networks» more  NN 2006»
15 years 6 months ago
A probabilistic model of gaze imitation and shared attention
An important component of language acquisition and cognitive learning is gaze imitation. Infants as young as one year of age can follow the gaze of an adult to determine the objec...
Matthew W. Hoffman, David B. Grimes, Aaron P. Shon...
JCB
2002
70views more  JCB 2002»
15 years 6 months ago
Strong Feature Sets from Small Samples
For small samples, classi er design algorithms typically suffer from over tting. Given a set of features, a classi er must be designed and its error estimated. For small samples, ...
Seungchan Kim, Edward R. Dougherty, Junior Barrera...