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NIPS
1994
13 years 7 months ago
Efficient Methods for Dealing with Missing Data in Supervised Learning
We present efficient algorithms for dealing with the problem of missing inputs (incomplete feature vectors) during training and recall. Our approach is based on the approximation ...
Volker Tresp, Ralph Neuneier, Subutai Ahmad
CIKM
2007
Springer
13 years 12 months ago
Developing learning strategies for topic-based summarization
Most up-to-date well-behaved topic-based summarization systems are built upon the extractive framework. They score the sentences based on the associated features by manually assig...
Ouyang You, Sujian Li, Wenjie Li
ICCV
2005
IEEE
13 years 11 months ago
Image Based Regression Using Boosting Method
We present a general algorithm of image based regression that is applicable to many vision problems. The proposed regressor that targets a multiple-output setting is learned using...
Shaohua Kevin Zhou, Bogdan Georgescu, Xiang Sean Z...
BMCBI
2006
126views more  BMCBI 2006»
13 years 5 months ago
A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data
Background: As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heteroge...
Zizhen Yao, Walter L. Ruzzo
TSP
2008
146views more  TSP 2008»
13 years 5 months ago
Improved M-FOCUSS Algorithm With Overlapping Blocks for Locally Smooth Sparse Signals
Abstract-- The FOCal Underdetermined System Solver (FOCUSS) algorithm has already found many applications in signal processing and data analysis, whereas the regularized MFOCUSS al...
Rafal Zdunek, Andrzej Cichocki