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AIRS
2010
Springer
15 years 4 months ago
Tuning Machine-Learning Algorithms for Battery-Operated Portable Devices
Machine learning algorithms in various forms are now increasingly being used on a variety of portable devices, starting from cell phones to PDAs. They often form a part of standard...
Ziheng Lin, Yan Gu, Samarjit Chakraborty
VLDB
2001
ACM
190views Database» more  VLDB 2001»
15 years 11 months ago
LEO - DB2's LEarning Optimizer
Most modern DBMS optimizers rely upon a cost model to choose the best query execution plan (QEP) for any given query. Cost estimates are heavily dependent upon the optimizer’s e...
Michael Stillger, Guy M. Lohman, Volker Markl, Mok...
KDD
2001
ACM
163views Data Mining» more  KDD 2001»
16 years 7 months ago
The "DGX" distribution for mining massive, skewed data
Skewed distributions appear very often in practice. Unfortunately, the traditional Zipf distribution often fails to model them well. In this paper, we propose a new probability di...
Zhiqiang Bi, Christos Faloutsos, Flip Korn
ICDM
2009
IEEE
198views Data Mining» more  ICDM 2009»
16 years 1 months ago
Information Extraction for Clinical Data Mining: A Mammography Case Study
Abstract—Breast cancer is the leading cause of cancer mortality in women between the ages of 15 and 54. During mammography screening, radiologists use a strict lexicon (BI-RADS) ...
Houssam Nassif, Ryan Woods, Elizabeth S. Burnside,...
ESANN
2007
15 years 8 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