4 papers
Byzantine-Resilient Federated Learning via QUBO-Based Client Selection on Quantum Annealers
Andras Ferenczi, Sutapa Samanta, Dagen Wang +1
Federated Learning (FL) trains a global model across decentralized clients while preserving data privacy, but at scale it is vulnerable to malicious updates. Byzantine-resilient ag…
Enhancing Federated Learning Privacy with QUBO
Andras Ferenczi, Sutapa Samanta, Dagen Wang +1
Federated learning (FL) is a widely used method for training machine learning (ML) models in a scalable way while preserving privacy (i.e., without centralizing raw data). Prior re…
Credit Default Prediction with Projected Quantum Feature Models and Ensembles
Andras Ferenczi, Dagen Wang, Mariya Bessonova +8
Accurate prediction of future loan defaults is a critical capability for financial institutions that provide lines of credit. For institutions that issue and manage extensive loan…
Realizing supersymmetry in a digitized quantum device
Sutapa Samanta, Jian-Xin Zhu, Armin Rahmani
The tricritical Ising model serves as an example of emergent spacetime supersymmetry, which can arise in condensed matter systems. In this work, we present a variational quantum al…