Nicholas Gisolfi

According to our database, Nicholas Gisolfi authored at least 12 papers between 2015 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Mitigating Persistent Client Dropout in Asynchronous Decentralized Federated Learning.

Ignacy Stepka, Nicholas Gisolfi, Kacper Trebacz, Artur Dubrawski

CoRR, August, 2025

2024

Signal Quality Auditing for Time-series Data.

Chufan Gao, Nicholas Gisolfi, Artur Dubrawski

CoRR, 2024

A SAT-Based Approach to Rigorous Verification of Bayesian Networks.

Ignacy Stepka, Nicholas Gisolfi, Artur Dubrawski

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2024

Data-Driven Discovery of Design Specifications (Student Abstract).

Angela Chen, Nicholas Gisolfi, Artur Dubrawski

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Verification of Fuzzy Decision Trees.

Jack H. Good, Nicholas Gisolfi, James Kyle Miller, Artur Dubrawski

IEEE Trans. Software Eng., 2023

Ordinal Programmatic Weak Supervision and Crowdsourcing for Estimating Cognitive States (Student Abstract).

Prakruthi Pradeep, Benedikt Boecking, Nicholas Gisolfi, Jacob R. Kintz, Torin K. Clark, Artur Dubrawski

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Model-Centric Verification of Artificial Intelligence.

Nicholas Gisolfi

PhD thesis, 2022

Actionable Model-Centric Explanations (Student Abstract).

Cecilia G. Morales, Nicholas Gisolfi, Robert Edman, James Kyle Miller, Artur Dubrawski

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Provably Robust Model-Centric Explanations for Critical Decision-Making.

Cecilia G. Morales, Nicholas Gisolfi, Robert Edman, James Kyle Miller, Artur Dubrawski

CoRR, 2021

2018

Revealing Actionable Simplicity in Data.

Nick Gisolfi, Artur Dubrawski

Proceedings of the 2018 AAAI Spring Symposia, 2018

2015

Finding Meaningful Gaps to Guide Data Acquisition for a Radiation Adjudication System.

Nick Gisolfi, Madalina Fiterau, Artur Dubrawski

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Leveraging Common Structure to Improve Prediction across Related Datasets.

Matt Barnes, Nick Gisolfi, Madalina Fiterau, Artur Dubrawski

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015