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BMCBI
2006
118views more  BMCBI 2006»
15 years 4 months ago
Identification of gene expression patterns using planned linear contrasts
Background: In gene networks, the timing of significant changes in the expression level of each gene may be the most critical information in time course expression profiles. With ...
Hao Li, Constance L. Wood, Yushu Liu, Thomas V. Ge...
INFOCOM
2011
IEEE
14 years 8 months ago
Secure and practical outsourcing of linear programming in cloud computing
—Cloud Computing has great potential of providing robust computational power to the society at reduced cost. It enables customers with limited computational resources to outsourc...
Cong Wang, Kui Ren, Jia Wang
ESANN
2008
15 years 6 months ago
A Regularized Learning Method for Neural Networks Based on Sensitivity Analysis
The Sensitivity-Based Linear Learning Method (SBLLM) is a learning method for two-layer feedforward neural networks, based on sensitivity analysis, that calculates the weights by s...
Bertha Guijarro-Berdiñas, Oscar Fontenla-Ro...
NIPS
2003
15 years 6 months ago
Multiple-Instance Learning via Disjunctive Programming Boosting
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
Stuart Andrews, Thomas Hofmann
163
Voted
CORR
2010
Springer
122views Education» more  CORR 2010»
15 years 4 months ago
Facility Location with Client Latencies: Linear-Programming based Techniques for Minimum-Latency Problems
We introduce a problem that is a common generalization of the uncapacitated facility location (UFL) and minimum latency (ML) problems, where facilities not only need to be opened ...
Deeparnab Chakrabarty, Chaitanya Swamy