activity
20182021
most citedReal-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems

10 citations · 10 across the 4 of their papers we have counts for

collaborators

13 papers

cs.LG2021

Detection of Dataset Shifts in Learning-Enabled Cyber-Physical Systems using Variational Autoencoder for Regression

Feiyang Cai, Ali I. Ozdagli, Xenofon Koutsoukos

Cyber-physical systems (CPSs) use learning-enabled components (LECs) extensively to cope with various complex tasks under high-uncertainty environments. However, the dataset shifts…

cs.LG2020

Byzantine Resilient Distributed Multi-Task Learning

Jiani Li, Waseem Abbas, Xenofon Koutsoukos

Distributed multi-task learning provides significant advantages in multi-agent networks with heterogeneous data sources where agents aim to learn distinct but correlated models sim…

eess.SY2020

Interplay Between Resilience and Accuracy in Resilient Vector Consensus in Multi-Agent Networks

Waseem Abbas, Mudassir Shabbir, Jiani Li +1

In this paper, we study the relationship between resilience and accuracy in the resilient distributed multi-dimensional consensus problem. We consider a network of agents, each of…

eess.SY2020

Strong Structural Controllability of Diffusively Coupled Networks: Comparison of Bounds Based on Distances and Zero Forcing

Yasin Yazicioglu, Mudassir Shabbir, Waseem Abbas +1

We study the strong structural controllability (SSC) of diffusively coupled networks, where the external control inputs are injected to only some nodes, namely the leaders. For suc…

cs.MA2020

Resilient Distributed Diffusion for Multi-task Estimation

Jiani Li, Xenofon Koutsoukos

Distributed diffusion is a powerful algorithm for multi-task state estimation which enables networked agents to interact with neighbors to process input data and diffuse informatio…

cs.MA2020

Resilient Distributed Diffusion in Networks with Adversaries

Jiani Li, Waseem Abbas, Xenofon Koutsoukos

In this paper, we study resilient distributed diffusion for multi-task estimation in the presence of adversaries where networked agents must estimate distinct but correlated states…