3 papers
cs.CY2026
Driving Accessibility: Shifting the Narrative & Design of Automated Vehicle Systems for Persons With Disabilities Through a Collaborative Scoring System
Savvy Barnes, Maricarmen Davis, Josh Siegel
Automated vehicles present unique opportunities and challenges, with progress and adoption limited, in part, by policy and regulatory barriers. Underrepresented groups, including i…
cs.LG2024
Pareto Data Framework: Steps Towards Resource-Efficient Decision Making Using Minimum Viable Data (MVD)
Tashfain Ahmed, Josh Siegel
This paper introduces the Pareto Data Framework, an approach for identifying and selecting the Minimum Viable Data (MVD) required for enabling machine learning applications on cons…
cs.LG2024
Impact of Network Topology on Byzantine Resilience in Decentralized Federated Learning
Siddhartha Bhattacharya, Daniel Helo, Joshua Siegel
Federated learning (FL) enables a collaborative environment for training machine learning models without sharing training data between users. This is typically achieved by aggregat…