Linear Discriminant Analysis (LDA) is a popular data-analytic tool for studying the class relationship between data points. A major disadvantage of LDA is that it fails to discove...
Deng Cai, Xiaofei He, Kun Zhou, Jiawei Han, Hujun ...
— It has previously been shown that ensembles of terminated protograph-based low-density parity-check (LDPC) convolutional codes have a typical minimum distance that grows linear...
David G. M. Mitchell, Michael Lentmaier, Daniel J....
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Motivated by the goal of factoring large integers using the Number Field Sieve, several special-purpose hardware designs have been recently proposed for solving large sparse system...
Willi Geiselmann, Adi Shamir, Rainer Steinwandt, E...
Abstract—Several contributions have been made so far to develop optimal multichannel linear filtering approaches and show their ability to reduce the acoustic noise. However, th...