This paper proposes a comprehensive modeling architecture for workloads on parallel computers using Markov chains in combination with state dependent empirical distribution functi...
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Brain machine interfaces work by mapping the relevant neural activity to the intended movement known as ‘decoding’. Here, we develop a recursive Bayesian decoder for goaldirec...
Maryam Modir Shanechi, Gregory W. Wornell, Ziv Wil...
In this paper, we propose a kernel backprojection method for computed tomography. The classical backprojection method estimates an unknown pixel value by the summation of the proj...
This paper investigates syntactic and sub-lexical features in Turkish discriminative language models (DLMs). DLM is a featurebased language modeling approach. It reranks the ASR o...
Ebru Arisoy, Murat Saraclar, Brian Roark, Izhak Sh...