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BMCBI
2008
136views more  BMCBI 2008»
13 years 8 months ago
Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models
Background: When predictive survival models are built from high-dimensional data, there are often additional covariates, such as clinical scores, that by all means have to be incl...
Harald Binder, Martin Schumacher
TSP
2008
151views more  TSP 2008»
13 years 8 months ago
Reduce and Boost: Recovering Arbitrary Sets of Jointly Sparse Vectors
The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...
Moshe Mishali, Yonina C. Eldar
SIGIR
2012
ACM
11 years 11 months ago
Boosting multi-kernel locality-sensitive hashing for scalable image retrieval
Similarity search is a key challenge for multimedia retrieval applications where data are usually represented in high-dimensional space. Among various algorithms proposed for simi...
Hao Xia, Pengcheng Wu, Steven C. H. Hoi, Rong Jin
ICML
2000
IEEE
14 years 9 months ago
A Boosting Approach to Topic Spotting on Subdialogues
We report the results of a study on topic spotting in conversational speech. Using a machine learning approach, we build classifiers that accept an audio file of conversational hu...
Kary Myers, Michael J. Kearns, Satinder P. Singh, ...
ICPR
2008
IEEE
14 years 3 months ago
Boosting performance for 2D Linear Discriminant Analysis via regression
Two Dimensional Linear Discriminant Analysis (2DLDA) has received much interest in recent years. However, 2DLDA could make pairwise distances between any two classes become signiï...
Nam Nguyen, Wanquan Liu, Svetha Venkatesh