Neural networks are vulnerable to adversarial examples and researchers have proposed
many heuristic attack and defense mechanisms. We address this problem through the …

While recent developments in autonomous vehicle (AV) technology highlight substantial
progress, we lack tools for rigorous and scalable testing. Real-world testing, the de facto …

Randomized features provide a computationally efficient way to approximate kernel machines
in machine learning tasks. However, such methods require a user-defined kernel as input. …

Time-resolved stereoscopic particle image velocimetry is used to investigate the structure of
the very-large-scale motions (VLSMs) in fully developed turbulent pipe flow. The motions …

While autonomous vehicle (AV) technology has shown substantial progress, we still lack
tools for rigorous and scalable testing. Real-world testing, the $\textit{de-facto}$ evaluation …

Automatic Sarcasm Detection in conversations is a difficult and tricky task. Classifying an
utterance as sarcastic or not in isolation can be futile since most of the time the sarcastic nature …

Background Context Lumbar spinal stenosis (LSS) is a prevalent and costly condition
associated with significant dysfunction. Alleviation of pain and improvement of function are the …

Learning-based methodologies increasingly find applications in safety-critical domains like
autonomous driving and medical robotics. Due to the rare nature of dangerous events, real-…

Balancing performance and safety is crucial to deploying autonomous vehicles in multi-agent
environments. In particular, autonomous racing is a domain that penalizes safe but …

Standard forms of coordinate and stochastic gradient methods do not adapt to structure in
data; their good behavior under random sampling is predicated on uniformity in data. When …