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» Labeling Points with Weights
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ICML
2003
IEEE
16 years 7 months ago
Learning with Positive and Unlabeled Examples Using Weighted Logistic Regression
The problem of learning with positive and unlabeled examples arises frequently in retrieval applications. We transform the problem into a problem of learning with noise by labelin...
Wee Sun Lee, Bing Liu
DATE
1999
IEEE
89views Hardware» more  DATE 1999»
15 years 10 months ago
A Methodology and Design Environment for DSP ASIC Fixed-Point Refinement
Complex signal processing algorithms are specified in floating point precision. When their hardware implementation requires fixed point precision, type refinement is needed. The p...
Radim Cmar, Luc Rijnders, Patrick Schaumont, Serge...
CSDA
2006
84views more  CSDA 2006»
15 years 6 months ago
Robust weighted LAD regression
The least squares linear regression estimator is well-known to be highly sensitive to unusual observations in the data, and as a result many more robust estimators have been propo...
Avi Giloni, Jeffrey S. Simonoff, Bhaskar Sengupta
ICML
2010
IEEE
15 years 7 months ago
Large Scale Max-Margin Multi-Label Classification with Priors
We propose a max-margin formulation for the multi-label classification problem where the goal is to tag a data point with a set of pre-specified labels. Given a set of L labels, a...
Bharath Hariharan, Lihi Zelnik-Manor, S. V. N. Vis...
PAMI
2006
128views more  PAMI 2006»
15 years 6 months ago
On Weighting Clustering
Recent papers and patents in iterative unsupervised learning have emphasized a new trend in clustering. It basically consists of penalizing solutions via weights on the instance po...
Richard Nock, Frank Nielsen