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JMLR
2008
230views more  JMLR 2008»
14 years 11 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
SC
2004
ACM
15 years 5 months ago
A Performance and Scalability Analysis of the BlueGene/L Architecture
This paper is structured as follows. Section 2 gives an architectural description of BlueGene/L. Section 3 analyzes the issue of “computational noise” – the effect that the o...
Kei Davis, Adolfy Hoisie, Greg Johnson, Darren J. ...
ESSMAC
2003
Springer
15 years 5 months ago
Analysis of Some Methods for Reduced Rank Gaussian Process Regression
Abstract. While there is strong motivation for using Gaussian Processes (GPs) due to their excellent performance in regression and classification problems, their computational com...
Joaquin Quiñonero Candela, Carl Edward Rasm...
ICML
2008
IEEE
16 years 17 days ago
Sequence kernels for predicting protein essentiality
The problem of identifying the minimal gene set required to sustain life is of crucial importance in understanding cellular mechanisms and designing therapeutic drugs. This work d...
Cyril Allauzen, Mehryar Mohri, Ameet Talwalkar
101
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ADBIS
2009
Springer
143views Database» more  ADBIS 2009»
15 years 6 months ago
Cost-Based Vectorization of Instance-Based Integration Processes
The inefficiency of integration processes—as an abstraction of workflow-based integration tasks—is often reasoned by low resource utilization and significant waiting times f...
Matthias Böhm, Dirk Habich, Steffen Preissler...