.png){kind=icon}
Return
A decomposition method for large-scale box constrained optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.amc.2013.12.169.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
A decomposition method for solving large-scale box constrained optimization is proposed. The algorithm is motivated by the successful use of the decomposition method presented by Joachims for training support vector machines. In particular, a new technique, based on the new definition KKT-violating index, is introduced for working set identification. Finally, the numerical experiments and implementation details show that this method is practical for large-scale problems. (C) 2014 Elsevier Inc. All rights reserved.
Keywords:
Box constrained optimization
Decomposition method
Working set identification
Large-scale
KKT-violating index
Journal
IF:
3.4
Papers:
2.3W
Citations:
3.3W
Organization
Cited Papers
ShareSaveShareSaveShareSaveOrigin of Structural Change Driven by A-Site Lanthanide Doping in ABO3-Type Perovskite Ferroelectrics.png)
Crystals
OAAI
CrystalsIF0
OAAIShareSaveApplying and Comparing LSTM and ARIMA to Predict CO Levels for a Time-Series Measurements in a Port AreaSignals
OAAI
SignalsIF0
OAAIShareSaveShareSave
View more