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GECCO
2010
Springer
169views Optimization» more  GECCO 2010»
15 years 10 months ago
Robust symbolic regression with affine arithmetic
We use affine arithmetic to improve both the performance and the robustness of genetic programming for symbolic regression. During evolution, we use affine arithmetic to analyze e...
Cassio Pennachin, Moshe Looks, João A. de V...
CSDA
2006
92views more  CSDA 2006»
15 years 6 months ago
Robust measures of tail weight
The kurtosis coefficient is often regarded as a measure of the tail heaviness of a distribution relative to that of the normal distribution. However, it also measures the peakedne...
Guy Brys, Mia Hubert, Anja Struyf
CSDA
2006
84views more  CSDA 2006»
15 years 6 months ago
Robust weighted LAD regression
The least squares linear regression estimator is well-known to be highly sensitive to unusual observations in the data, and as a result many more robust estimators have been propo...
Avi Giloni, Jeffrey S. Simonoff, Bhaskar Sengupta
JPDC
2008
122views more  JPDC 2008»
15 years 6 months ago
Stochastic robustness metric and its use for static resource allocations
This research investigates the problem of robust static resource allocation for distributed computing systems operating under imposed Quality of Service (QoS) constraints. Often, ...
Vladimir Shestak, Jay Smith, Anthony A. Maciejewsk...
ICDM
2010
IEEE
167views Data Mining» more  ICDM 2010»
15 years 4 months ago
Averaged Stochastic Gradient Descent with Feedback: An Accurate, Robust, and Fast Training Method
On large datasets, the popular training approach has been stochastic gradient descent (SGD). This paper proposes a modification of SGD, called averaged SGD with feedback (ASF), tha...
Xu Sun, Hisashi Kashima, Takuya Matsuzaki, Naonori...