19 citations · 51 across the 13 of their papers we have counts for
3 papers · 1 filter
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…
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…
Developing a Taxonomy of Elements Adversarial to Autonomous Vehicles
Mohammadali Saffary, Nishan Inampudi, Joshua E. Siegel
As highly automated vehicles reach higher deployment rates, they find themselves in increasingly dangerous situations. Knowing that the consequence of a crash is significant for th…