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CVPR
2010
IEEE
14 years 5 months ago
Online Multiple Instance Learning with No Regret
Multiple instance (MI) learning is a recent learning paradigm that is more flexible than standard supervised learning algorithms in the handling of label ambiguity. It has been u...
Li Mu, James Kwok, Lu Bao-liang

Publication
273views
13 years 3 months ago
 3D Visualization of Multiple Time Series on Maps
Abstract—In the analysis of spatially-referenced timedependent data, gaining an understanding of the spatiotemporal distributions and relationships among the attributes in the...
Sidharth Thakur, Andrew J. Hanson
ICPR
2000
IEEE
14 years 1 months ago
Design of Effective Multiple Classifier Systems by Clustering of Classifiers
In the field of pattern recognition, multiple classifier systems based on the combination of outputs of a set of different classifiers have been proposed as a method for the devel...
Giorgio Giacinto, Fabio Roli, Giorgio Fumera
ICML
2007
IEEE
14 years 10 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
SI3D
2010
ACM
14 years 4 months ago
Frankenrigs: building character rigs from multiple sources
We present a new rigging and skinning method which uses a database of partial rigs extracted from a set of source characters. Given a target mesh and a set of joint locations, our...
Christian Miller, Okan Arikan, Don Fussell