681 citations · 1.6k across the 51 of their papers we have counts for
8 papers · 1 filter
Label Shift Estimation With Incremental Prior Update
Yunrui Zhang, Gustavo Batista, Salil S. Kanhere
An assumption often made in supervised learning is that the training and testing sets have the same label distribution. However, in real-life scenarios, this assumption rarely hold…
Instance-Wise Monotonic Calibration by Constrained Transformation
Yunrui Zhang, Gustavo Batista, Salil S. Kanhere
Deep neural networks often produce miscalibrated probability estimates, leading to overconfident predictions. A common approach for calibration is fitting a post-hoc calibration ma…
Adversarially Guided Stateful Defense Against Backdoor Attacks in Federated Deep Learning
Hassan Ali, Surya Nepal, Salil S. Kanhere +1
Recent works have shown that Federated Learning (FL) is vulnerable to backdoor attacks. Existing defenses cluster submitted updates from clients and select the best cluster for agg…
Contextual Chart Generation for Cyber Deception
David D. Nguyen, David Liebowitz, Surya Nepal +2
Honeyfiles are security assets designed to attract and detect intruders on compromised systems. Honeyfiles are a type of honeypot that mimic real, sensitive documents, creating the…
Multiple Hypothesis Dropout: Estimating the Parameters of Multi-Modal Output Distributions
David D. Nguyen, David Liebowitz, Surya Nepal +1
In many real-world applications, from robotics to pedestrian trajectory prediction, there is a need to predict multiple real-valued outputs to represent several potential scenarios…
Discretization-based ensemble model for robust learning in IoT
Anahita Namvar, Chandra Thapa, Salil S. Kanhere
IoT device identification is the process of recognizing and verifying connected IoT devices to the network. This is an essential process for ensuring that only authorized devices c…