This paper addresses the challenging problem of similarity search over widely distributed ultra-high dimensional data. Such an application is retrieval of the top-k most similar d...
In this paper, we propose two novel techniques, which successfully address several major problems in the field of particle swarm optimization (PSO) and promise a significant breakt...
Serkan Kiranyaz, Turker Ince, E. Alper Yildirim, M...
Dwarf is a highly compressed structure for computing, storing, and querying data cubes. Dwarf identifies prefix and suffix structural redundancies and factors them out by coalesci...
Yannis Sismanis, Antonios Deligiannakis, Nick Rous...
We propose an Isometric Self-Organizing Map (ISOSOM) method for nonlinear dimensionality reduction, which integrates a Self-Organizing Map model and an ISOMAP dimension reduction ...
We propose an unconventional but highly effective approach
to robust fitting of multiple structures by using statistical
learning concepts. We design a novel Mercer kernel
for t...