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ECML
2006
Springer
13 years 11 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
IJHPCA
2010
105views more  IJHPCA 2010»
13 years 6 months ago
A Pipelined Algorithm for Large, Irregular All-Gather Problems
We describe and evaluate a new, pipelined algorithm for large, irregular all-gather problems. In the irregular all-gather problem each process in a set of processes contributes in...
Jesper Larsson Träff, Andreas Ripke, Christia...
ICML
2004
IEEE
14 years 8 months ago
A needle in a haystack: local one-class optimization
This paper addresses the problem of finding a small and coherent subset of points in a given data. This problem, sometimes referred to as one-class or set covering, requires to fi...
Koby Crammer, Gal Chechik
BMCBI
2010
112views more  BMCBI 2010»
13 years 7 months ago
Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships
Background: The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. Wh...
Junhee Seok, Amit Kaushal, Ronald W. Davis, Wenzho...

Publication
197views
12 years 3 months ago
Convex non-negative matrix factorization for massive datasets
Non-negative matrix factorization (NMF) has become a standard tool in data mining, information retrieval, and signal processing. It is used to factorize a non-negative data matrix ...
C. Thurau, K. Kersting, M. Wahabzada, and C. Bauck...