In this research, a systematic study is conducted of four dimension reduction techniques for the text clustering problem, using five benchmark data sets. Of the four methods -- Ind...
Bin Tang, Michael A. Shepherd, Malcolm I. Heywood,...
Locally linear embedding (LLE) is a recently proposed method for unsupervised nonlinear dimensionality reduction. It has a number of attractive features: it does not require an ite...
Dick de Ridder, Olga Kouropteva, Oleg Okun, Matti ...
This paper presents a probabilistic framework for computing correspondences and fundamental matrix in the structure from motion problem. Inspired by Moisan and Stival [1], we sugg...
Real-world data sets such as recordings from functional magnetic resonance imaging often possess both spatial and temporal structure. Here, we propose an algorithm including such ...
Fabian J. Theis, Peter Gruber, Ingo R. Keck, Elmar...
Let I be a random 3CNF formula generated by choosing a truth assignment for variables x1, . . . , xn uniformly at random and including every clause with i literals set true by w...