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» Evaluating algorithms that learn from data streams
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SIGMOD
2006
ACM
137views Database» more  SIGMOD 2006»
16 years 20 days ago
Optimal multi-scale patterns in time series streams
We introduce a method to discover optimal local patterns, which concisely describe the main trends in a time series. Our approach examines the time series at multiple time scales ...
Spiros Papadimitriou, Philip S. Yu
ICIAP
2005
ACM
16 years 19 days ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti...
KDD
2006
ACM
155views Data Mining» more  KDD 2006»
16 years 28 days ago
Single-pass online learning: performance, voting schemes and online feature selection
To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such a...
Vitor R. Carvalho, William W. Cohen
BMCBI
2008
228views more  BMCBI 2008»
15 years 19 days ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
114
Voted
DAWAK
2005
Springer
15 years 6 months ago
A Decremental Algorithm for Maintaining Frequent Itemsets in Dynamic Databases
Data mining and machine learning must confront the problem of pattern maintenance because data updating is a fundamental operation in data management. Most existing data-mining alg...
Shichao Zhang, Xindong Wu, Jilian Zhang, Chengqi Z...