4 papers
Mitigating Persistent Client Dropout in Asynchronous Decentralized Federated Learning
Ignacy Stępka, Nicholas Gisolfi, Kacper Trębacz +1
We consider the problem of persistent client dropout in asynchronous Decentralized Federated Learning (DFL). Asynchronicity and decentralization obfuscate information about model u…
A SAT-based approach to rigorous verification of Bayesian networks
Ignacy Stępka, Nicholas Gisolfi, Artur Dubrawski
Recent advancements in machine learning have accelerated its widespread adoption across various real-world applications. However, in safety-critical domains, the deployment of mach…
Signal Quality Auditing for Time-series Data
Chufan Gao, Nicholas Gisolfi, Artur Dubrawski
Signal quality assessment (SQA) is required for monitoring the reliability of data acquisition systems, especially in AI-driven Predictive Maintenance (PMx) application contexts. S…
Provably Robust Model-Centric Explanations for Critical Decision-Making
Cecilia G. Morales, Nicholas Gisolfi, Robert Edman +2
We recommend using a model-centric, Boolean Satisfiability (SAT) formalism to obtain useful explanations of trained model behavior, different and complementary to what can be glean…