In this work we consider the problem of universal prediction of individual sequences where the universal predictor is a deterministic finite state machine, with a fixed, relativel...
In this paper, we study efficient closed pattern mining in a general framework of set systems, which are families of subsets ordered by set-inclusion with a certain structure, pro...
Visualisations of dynamic data change in appearance over time, reflecting changes in the underlying data, be that the development of a social network, or the addition or removal o...
Abstract— We applied Support Vector Machines to the prediction of the subcellular localization of transmembrane proteins, and compared the performance of different sequence kerne...
Stefan Maetschke, Marcus Gallagher, Mikael Bod&eac...
This work investigates the use of nonlinear dependencies in natural image sequence statistics to learn higher-order structures in natural videos. We propose a two-layer model that...