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» Testing and Spot-Checking of Data Streams
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SDM
2007
SIAM
198views Data Mining» more  SDM 2007»
13 years 10 months ago
Learning from Time-Changing Data with Adaptive Windowing
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Albert Bifet, Ricard Gavaldà
JLP
2000
109views more  JLP 2000»
13 years 8 months ago
Demand Transformation Analysis for Concurrent Constraint Programs
interpretation. In the context of stream parallelism, this analysis identi es an amount of input data for which predicate execution can safely wait without danger of introducing de...
Moreno Falaschi, Patrick Hicks, William H. Winsbor...
ICS
2010
Tsinghua U.
14 years 6 months ago
Space-Efficient Estimation of Robust Statistics and Distribution Testing
: The generic problem of estimation and inference given a sequence of i.i.d. samples has been extensively studied in the statistics, property testing, and learning communities. A n...
Steve Chien, Katrina Ligett, Andrew McGregor
SDM
2009
SIAM
144views Data Mining» more  SDM 2009»
14 years 5 months ago
On Segment-Based Stream Modeling and Its Applications.
The primary constraint in the effective mining of data streams is the large volume of data which must be processed in real time. In many cases, it is desirable to store a summary...
Charu C. Aggarwal
MASCOTS
2004
13 years 10 months ago
Architecture Independent Performance Characterization and Benchmarking for Scientific Applications
A simple, tunable, synthetic benchmark with a performance directly related to applications would be of great benefit to the scientific computing community. In this paper, we prese...
Erich Strohmaier, Hongzhang Shan