31 citations · 39 across the 8 of their papers we have counts for
8 papers
Trust or Bust: A Survey of Threats in Decentralized Wireless Networks
Hetvi Shastri, Akanksha Atrey, Andre Beck +1
The recent emergence of decentralized wireless networks empowers individual entities to own, operate, and offer subscriptionless connectivity services in exchange for monetary comp…
Can Large Language Models Learn Formal Logic? A Data-Driven Training and Evaluation Framework
Yuan Xia, Akanksha Atrey, Fadoua Khmaissia +1
This paper investigates the logical reasoning capabilities of large language models (LLMs). For a precisely defined yet tractable formulation, we choose the conceptually simple but…
W4-Groups: Modeling the Who, What, When and Where of Group Behavior via Mobility Sensing
Akanksha Atrey, Camellia Zakaria, Rajesh Balan +1
Human social interactions occur in group settings of varying sizes and locations, depending on the type of social activity. The ability to distinguish group formations based on the…
SODA: Protecting Proprietary Information in On-Device Machine Learning Models
Akanksha Atrey, Ritwik Sinha, Saayan Mitra +1
The growth of low-end hardware has led to a proliferation of machine learning-based services in edge applications. These applications gather contextual information about users and…
Preserving Privacy in Personalized Models for Distributed Mobile Services
Akanksha Atrey, Prashant Shenoy, David Jensen
The ubiquity of mobile devices has led to the proliferation of mobile services that provide personalized and context-aware content to their users. Modern mobile services are distri…
New Frontiers in IoT: Networking, Systems, Reliability, and Security Challenges
Saurabh Bagchi, Tarek F. Abdelzaher, Ramesh Govindan +4
The field of IoT has blossomed and is positively influencing many application domains. In this paper, we bring out the unique challenges this field poses to research in computer sy…
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning
Akanksha Atrey, Kaleigh Clary, David Jensen
Saliency maps are frequently used to support explanations of the behavior of deep reinforcement learning (RL) agents. However, a review of how saliency maps are used in practice in…
Measuring and Characterizing Generalization in Deep Reinforcement Learning
Sam Witty, Jun Ki Lee, Emma Tosch +3
Deep reinforcement-learning methods have achieved remarkable performance on challenging control tasks. Observations of the resulting behavior give the impression that the agent has…