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Speech-based degree of sleepiness estimation is an emerging research problem. In the literature, this problem has been mainly addressed through modeling of low level of descriptors. This paper investigates an end-to-end approach, where given raw waveform a ...
There has been growing interest in studying connections between generalization error of learning algorithms and information measures. In this work, we generalize a result that employs the maximal leakage, a measure of leakage of information, and explore ho ...
We present a deep architecture and learning framework for establishing correspondences across cross-spectral visible and infrared images in an unpaired setting. To overcome the unpaired cross-spectral data problem, we design the unified image translation a ...
This paper presents a novel deep architecture for weakly-supervised temporal action localization that not only generates segment-level action responses but also propagates segment-level responses to the neighborhood in a form of graph Laplacian regularizat ...
GRADES-NDA 2019 is the second joint meeting of the GRADES and NDA workshops, which were each independently organized at previous SIGMOD-PODS meetings, GRADES since 2013 and NDA since 2016. The focus of GRADES-NDA is the application areas, usage scenarios, ...
In this paper, we consider the set of interfaces between + and - spins arising for the critical planar Ising model on a domain with + boundary conditions, and show that it converges to nested CLE3. Our proof relies on the study of the coupling between the ...
Data is pervasive in today's world and has actually been for quite some time. With the increasing volume of data to process, there is a need for faster and at least as accurate techniques than what we already have. In particular, the last decade recorded t ...
Aerial videos taken by a drone not too far above the surface may contain the drone's shadow projected on the scene. This deteriorates the aesthetic quality of videos. With the presence of other shadows, shadow removal cannot be directly applied, and the sh ...
This study investigates the performance of an updated version of our pre-impact detection algorithm while parsing out hip kinematics in order to identify unexpected tripping-like perturbations during walking. This approach grounds on the hypothesis that du ...
Capturing students' behavioral patterns through analysis of sequential interaction logs, is an important task in educational data mining to enable more effective personalized support during the learning process. This study aims at discovery and temporal an ...
