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SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
13 years 6 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
NECO
2010
136views more  NECO 2010»
15 years 2 months ago
Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines
To allow the hidden units of a restricted Boltzmann machine to model the transformation between two successive images, Memisevic and Hinton (2007) introduced three-way multiplicat...
Roland Memisevic, Geoffrey E. Hinton
SEKE
2004
Springer
15 years 9 months ago
Supporting the Requirements Prioritization Process. A Machine Learning approach
Requirements prioritization plays a key role in the requirements engineering process, in particular with respect to critical tasks such as requirements negotiation and software re...
Paolo Avesani, Cinzia Bazzanella, Anna Perini, Ang...
APBC
2003
128views Bioinformatics» more  APBC 2003»
15 years 5 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won
BMCBI
2008
123views more  BMCBI 2008»
15 years 4 months ago
Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach
Background: Eukaryotic promoter prediction using computational analysis techniques is one of the most difficult jobs in computational genomics that is essential for constructing a...
Firoz Anwar, Syed Murtuza Baker, Taskeed Jabid, Md...