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» Introduction to Randomized Algorithms
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ICML
2008
IEEE
16 years 7 months ago
An empirical evaluation of supervised learning in high dimensions
In this paper we perform an empirical evaluation of supervised learning on highdimensional data. We evaluate performance on three metrics: accuracy, AUC, and squared loss and stud...
Rich Caruana, Nikolaos Karampatziakis, Ainur Yesse...
ICML
2005
IEEE
16 years 7 months ago
Generalized skewing for functions with continuous and nominal attributes
This paper extends previous work on skewing, an approach to problematic functions in decision tree induction. The previous algorithms were applicable only to functions of binary v...
Soumya Ray, David Page
ICASSP
2009
IEEE
16 years 27 days ago
Estimating multiple transmitter locations from power measurements at multiple receivers
We consider the estimation of the locations of multiple transmitters based on received signal strength measurements at a network of randomly-placed receivers. We generalize the ex...
Jill K. Nelson, Jaime E. Almodovar, Maya R. Gupta,...
CEC
2008
IEEE
16 years 18 days ago
Multi-level neutrality in optimization
Abstract— This paper explores the idea of neutrality in heuristic optimization algorithms. In particular, the effect of having multiple levels of neutrality in representations is...
Colin G. Johnson
CISS
2007
IEEE
16 years 14 days ago
Coverage-Based Information Retrieval for Lifetime Maximization in Sensor Networks
—We consider information retrieval in a wireless sensor network deployed to monitor a spatially correlated random field. We address sensor scheduling in each data collection und...
Tong Zhao, Qing Zhao