Abstract— We consider discrete-time channels with finitelength intersymbol interference and additive Gaussian noise. The channel noise is considered to be a stationary ARMA (aut...
This work proposes to learn visual encodings of attention patterns that enables sequential attention for object detection in real world environments. The system embeds a saccadic d...
Refactoring of UML class diagrams is an emerging research topic and heavily inspired by refactoring of program code written in object-oriented implementation languages. Current cla...
Although speech and language processing techniques achieved a relative maturity during the last decade, designing a spoken dialogue system is still a tailoring task because of the ...
We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...