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ESANN
2007
13 years 9 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
BMCBI
2010
135views more  BMCBI 2010»
13 years 8 months ago
Delineation of amplification, hybridization and location effects in microarray data yields better-quality normalization
Background: Oligonucleotide arrays have become one of the most widely used high-throughput tools in biology. Due to their sensitivity to experimental conditions, normalization is ...
Marc Hulsman, Anouk Mentink, Eugene P. van Someren...
ASPLOS
1998
ACM
14 years 3 days ago
A Cost-Effective, High-Bandwidth Storage Architecture
This paper describes the Network-Attached Secure Disk (NASD) storage architecture, prototype implementations of NASD drives, array management for our architecture, and three files...
Garth A. Gibson, David Nagle, Khalil Amiri, Jeff B...
IPPS
1999
IEEE
14 years 5 days ago
The Impact of Memory Hierarchies on Cluster Computing
Using off-the-shelf commodity workstations and PCs to build a cluster for parallel computing has become a common practice. A choice of a cost-effective cluster computing platform ...
Xing Du, Xiaodong Zhang
CODES
2009
IEEE
14 years 2 months ago
An on-chip interconnect and protocol stack for multiple communication paradigms and programming models
A growing number of applications, with diverse requirements, are integrated on the same System on Chip (SoC) in the form of hardware and software Intellectual Property (IP). The d...
Andreas Hansson, Kees Goossens