Artificial Intelligence (AI) algorithms are increasingly providing decision making and
operational support across multiple domains. AI includes a wide (and growing) library of …

The recent O-RAN specifications promote the evolution of RAN architecture by function
disaggregation, adoption of open interfaces, and instantiation of a hierarchical closed-loop …

Deep learning has been successfully applied to solve various complex problems ranging
from big data analytics to computer vision and human-level control. Deep learning advances …

Techniques for creating and manipulating multimedia information have progressed to the
point where they can now ensure a high degree of realism. DeepFake is a generative deep …

Backdoors can be injected to NLP models such that they misbehave when the trigger words
or sentences appear in an input sample. Detecting such backdoors given only a subject …

Many existing backdoor scanners work by finding a small and fixed trigger. However,
advanced attacks have large and pervasive triggers, rendering existing scanners less …

Inspired by human intelligence, the research on online continual learning aims to push the
limits of the machine learning models to constantly learn from sequentially encountered …

Many important questions about a model cannot be answered just by explaining how much
each feature contributes to its output. To answer a broader set of questions, we generalize a …

Deep Neural Networks are actively being used in the design of autonomous Cyber-Physical
Systems (CPSs). The advantage of these models is their ability to handle high-dimensional …

Detecting anomalous inputs, such as adversarial and out-of-distribution (OOD) inputs, is
critical for classifiers (including deep neural networks or DNNs) deployed in real-world …