A statistical framework for modeling and prediction of binary matrices is presented. The method is applied to social network analysis, specifically the database of US Supreme Cou...
Eric Wang, Jorge Silva, Rebecca Willett, Lawrence ...
For compressive sensing, we endeavor to improve the recovery performance of the existing orthogonal matching pursuit (OMP) algorithm. To achieve a better estimate of the underlyin...
Saikat Chatterjee, Dennis Sundman, Mikael Skoglund
In this paper, to automatically generate musical thumbnails that contain the main part of the original tune, we propose a new estimation method for identifying structure changes i...
This paper investigates the impact of subspace based techniques for acoustic modeling in automatic speech recognition (ASR). There are many well known approaches to subspace based...
Fingerprint scanners have unique patterns that can be used to distinguish one scanner from another one. The pattern, which we call scanner pattern, stems from the variability of d...
Malicious data attacks to the real-time electricity market are studied. In particular, an adversary launches an attack by manipulating data from a set of meters with the goal of i...
This paper addresses the problem of acoustic echo cancellation in non-linear environments. The rst contribution relates to the use of a cascaded model which divides the loudspeake...
Moctar Mossi Idrissa, Christelle Yemdji, Nicholas ...
A new method for scale-aware saliency detection is introduced in this work. Scale determination is realized through a fast scale-space algorithm using color and texture. Scale inf...
In this study, we employed our recently developed iterative independent component analysis (iICA) procedure to measure single-trial EPs from auditory N100 recordings of 21 normal ...
In this paper, we describe a physical activity classification system using a body sensor network (BSN) consisting of costsensitive tri-axial accelerometers. We focus on workspace...
Natali Ruchansky, Claire Lochner, Elizabeth Do, Tr...