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BMCBI
2006
137views more  BMCBI 2006»
13 years 7 months ago
A classification-based framework for predicting and analyzing gene regulatory response
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...
RECOMB
2007
Springer
14 years 7 months ago
An Efficient and Accurate Graph-Based Approach to Detect Population Substructure
Currently, large-scale projects are underway to perform whole genome disease association studies. Such studies involve the genotyping of hundreds of thousands of SNP markers. One o...
Srinath Sridhar, Satish Rao, Eran Halperin
AAAI
2010
13 years 9 months ago
G-Optimal Design with Laplacian Regularization
In many real world applications, labeled data are usually expensive to get, while there may be a large amount of unlabeled data. To reduce the labeling cost, active learning attem...
Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, L...
IJSI
2008
156views more  IJSI 2008»
13 years 7 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker
ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
13 years 5 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava