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» A new evolutionary method for time series forecasting
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CCGRID
2005
IEEE
14 years 1 months ago
Fast pattern-based throughput prediction for TCP bulk transfers
The ability to quickly predict the throughput of a TCP transfer between a client and a server, or between peers, has wide application in scientific computing and commercial compu...
Tsung-i Huang, Jaspal Subhlok
TON
2010
167views more  TON 2010»
13 years 2 months ago
A Machine Learning Approach to TCP Throughput Prediction
TCP throughput prediction is an important capability in wide area overlay and multi-homed networks where multiple paths may exist between data sources and receivers. In this paper...
Mariyam Mirza, Joel Sommers, Paul Barford, Xiaojin...
CSDA
2006
84views more  CSDA 2006»
13 years 7 months ago
Extremal financial risk models and portfolio evaluation
It is difficult to find an existing single model which is able to simultaneously model exceedances over thresholds in multivariate financial time series. A new modeling approach, ...
Zhengjun Zhang, James Huang
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 9 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
EMO
2005
Springer
194views Optimization» more  EMO 2005»
14 years 1 months ago
An EMO Algorithm Using the Hypervolume Measure as Selection Criterion
Abstract. The hypervolume measure is one of the most frequently applied measures for comparing the results of evolutionary multiobjective optimization algorithms (EMOA). The idea t...
Michael Emmerich, Nicola Beume, Boris Naujoks