Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional d...
Motivated by Ajtai’s worst-case to average-case reduction for lattice problems, we study the complexity of computing short linearly independent vectors (short basis) in a lattic...
Using a novel data dimension reduction method proposed in statistics, we develop an appearance-based face recognition algorithm which is insensitive to large variation in lighting...
Yangrong Ling, Xiangrong Yin, Suchendra M. Bhandar...
The verification of quantitative aspects like performance and dependability by means of model checking has become an important and vivid area of research over the past decade. An ...
Stefan Blom, Boudewijn R. Haverkort, Matthias Kunt...
This paper reports on an improvement of Matsui’s linear cryptanalysis that reduces the complexity of an attack with algorithm 2, by taking advantage of the Fast Fourier Transform...