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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
15 years 11 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
BMCBI
2004
112views more  BMCBI 2004»
14 years 10 months ago
Predicting co-complexed protein pairs using genomic and proteomic data integration
Background: Identifying all protein-protein interactions in an organism is a major objective of proteomics. A related goal is to know which protein pairs are present in the same p...
Lan V. Zhang, Sharyl L. Wong, Oliver D. King, Fred...
NIPS
2007
14 years 12 months ago
Learning and using relational theories
Much of human knowledge is organized into sophisticated systems that are often called intuitive theories. We propose that intuitive theories are mentally represented in a logical ...
Charles Kemp, Noah Goodman, Joshua B. Tenenbaum
BMCBI
2007
207views more  BMCBI 2007»
14 years 10 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 2 months ago
Identification of weak motifs in multiple biological sequences using genetic algorithm
Recognition of motifs in multiple unaligned sequences provides an insight into protein structure and function. The task of discovering these motifs is very challenging because mos...
Topon Kumar Paul, Hitoshi Iba