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166
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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
114
Voted
COLT
2005
Springer
15 years 5 months ago
Data Dependent Concentration Bounds for Sequential Prediction Algorithms
Abstract. We investigate the generalization behavior of sequential prediction (online) algorithms, when data are generated from a probability distribution. Using some newly develop...
Tong Zhang
128
Voted
AIME
2003
Springer
15 years 8 months ago
The NewGuide Project: Guidelines, Information Sharing and Learning from Exceptions
Among the well agreed-on benefits of a guideline computerisation, with respect to the traditional text format, there are the disambiguation, the possibility of looking at the guide...
Paolo Ciccarese, Ezio Caffi, Lorenzo Boiocchi, Ass...
121
Voted
JCDL
2006
ACM
119views Education» more  JCDL 2006»
15 years 9 months ago
Learning from artifacts: metadata utilization analysis
Describes the MARC Content Designation Utilization Project, which is examining a very large set of metadata records as artifacts of the library cataloging enterprise. This is the ...
William E. Moen, Shawne D. Miksa, Amy Eklund, Serh...
140
Voted
WAPCV
2007
Springer
15 years 9 months ago
Language Label Learning for Visual Concepts Discovered from Video Sequences
Computational models of grounded language learning have been based on the premise that words and concepts are learned simultaneously. Given the mounting cognitive evidence for conc...
Prithwijit Guha, Amitabha Mukerjee