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Feature Engineering and Classifier Ensemble for KDD Cup 2010
KDD Cup 2010 is an educational data mining competition. Participants are asked to learn a model from students' past behavior and then predict their future performance. At National Taiwan University,Expand
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A tutorial on ν-support vector machines: Research Articles
TLDR
We briefly describe the main ideas of statistical learning theory, support vector machines (SVMs), and kernel feature spaces, including details of the algorithm and its implementation, theoretical results, and practical applications. Expand
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Enhanced resonant raman scattering and electron-phonon coupling from self-assembled secondary ZnO nanoparticles.
Self-assembled secondary ZnO nanoparticles, recognized with the agglomeration of crystalline subcrystals, are successfully synthesized by a simple sol-gel method. TEM images display that oneExpand
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A tutorial on n-support vector machines
TLDR
SUMMARY We briefly describe the main ideas of statistical learning theory, support vector machines (SVMs), and kernel feature spaces. Expand
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Relaxed Cutting Plane Method for Solving Linear Semi-Infinite Programming Problems
One of the major computational tasks of using the traditional cutting plane approach to solve linear semi-infinite programming problems lies in finding a global optimizer of a nonlinear and nonconvexExpand
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Built-In Current Sensor for IDDQ Test in CMOS
TLDR
This paper presents a current sensor circuit which can be built into a CMOS logic circuit to pelform a self test for leakage current. Expand
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A note on the decomposition methods for support vector regression
TLDR
The dual formulation of support vector regression involves with two closely related sets of variables. Expand
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Supplementary Materials for “ Newton Methods for Convolutional Neural Networks ”
n The total number of weights and biases. a Height of the input image at the mth layer (1 ≤ m ≤ L). apad Height of the image after padding at the mth layer (1 ≤ m ≤ L). aconv Height of the imageExpand
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