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» Evaluating algorithms that learn from data streams
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KDD
1998
ACM
190views Data Mining» more  KDD 1998»
15 years 2 months ago
Time Series Forecasting from High-Dimensional Data with Multiple Adaptive Layers
This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...
R. Bharat Rao, Scott Rickard, Frans Coetzee
DATE
2009
IEEE
171views Hardware» more  DATE 2009»
15 years 5 months ago
Automatic generation of streaming datapaths for arbitrary fixed permutations
Abstract—This paper presents a technique to perform arbitrary fixed permutations on streaming data. We describe a parameterized architecture that takes as input n data points st...
Peter A. Milder, James C. Hoe, Markus Püschel
CIKM
2006
Springer
15 years 4 days ago
Efficient range-constrained similarity search on wavelet synopses over multiple streams
Due to the resource limitation in the data stream environment, it has been reported that answering user queries according to the wavelet synopsis of a stream is an essential abili...
Hao-Ping Hung, Ming-Syan Chen
IJCSA
2006
121views more  IJCSA 2006»
14 years 10 months ago
Evaluation of the RC4 Algorithm for Data Encryption
Analysis of the effect of different parameters of the RC4 encryption algorithm where examined. Some experimental work was performed to illustrate the performance of this algorithm...
Allam Mousa, Ahmad Hamad
132
Voted
JMLR
2012
13 years 18 days ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee