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104
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SBIA
2004
Springer
15 years 8 months ago
Learning with Drift Detection
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Pedro Medas, Gladys Castillo, Pe...
125
Voted
JSAC
2010
107views more  JSAC 2010»
15 years 1 months ago
Online learning in autonomic multi-hop wireless networks for transmitting mission-critical applications
Abstract—In this paper, we study how to optimize the transmission decisions of nodes aimed at supporting mission-critical applications, such as surveillance, security monitoring,...
Hsien-Po Shiang, Mihaela van der Schaar
145
Voted
ML
2010
ACM
127views Machine Learning» more  ML 2010»
15 years 1 months ago
Stability and model selection in k-means clustering
Abstract Clustering Stability methods are a family of widely used model selection techniques for data clustering. Their unifying theme is that an appropriate model should result in...
Ohad Shamir, Naftali Tishby
IJCNN
2006
IEEE
15 years 8 months ago
Sparse Bayesian Models: Bankruptcy-Predictors of Choice?
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...
Bernardete Ribeiro, Armando Vieira, João Ca...
211
Voted
VLDB
2008
ACM
170views Database» more  VLDB 2008»
16 years 2 months ago
A multi-ranker model for adaptive XML searching
The evolution of computing technology suggests that it has become more feasible to offer access to Web information in a ubiquitous way, through various kinds of interaction device...
Ho Lam Lau, Wilfred Ng