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NN
2006
Springer
163views Neural Networks» more  NN 2006»
13 years 10 months ago
Machine learning approaches for estimation of prediction interval for the model output
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Durga L. Shrestha, Dimitri P. Solomatine
DAC
2006
ACM
14 years 11 months ago
MARS-C: modeling and reduction of soft errors in combinational circuits
Due to the shrinking of feature size and reduction in supply voltages, nanoscale circuits have become more susceptible to radiation induced transient faults. In this paper, we pre...
Natasa Miskov-Zivanov, Diana Marculescu
JMLR
2010
104views more  JMLR 2010»
13 years 4 months ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic
INFOCOM
2010
IEEE
13 years 8 months ago
A Frequency Domain Model to Predict the Estimation Accuracy of Packet Sampling
—In network measurement systems, packet sampling techniques are usually adopted to reduce the overall amount of data to collect and process. Being based on a subset of packets, t...
Luigi Alfredo Grieco, Chadi Barakat
ICC
2007
IEEE
128views Communications» more  ICC 2007»
14 years 4 months ago
An Efficient Selective Receiver for STBC Scheme
—In this paper, we propose an efficient selective receiver for space-time block coding (STBC) scheme. In this proposed scheme, we divide the received signals into two groups. By ...
Lijun Liu, Sooyoung Kim, Myoung-Seob Lim