David J. Love

Latency Optimization for Blockchain-Empowered Federated Learning in Multi-Server Edge Computing

2022 · arXiv (Cornell University)

In this paper, we study a new latency optimization problem for blockchain-based federated learning (BFL) in multi-server edge computing. In this system model, distributed mobile devices (MDs) communicate with a set of edge servers (ESs) …

Defending Adversarial Attacks on Deep Learning Based Power Allocation in Massive MIMO Using Denoising Autoencoders

2022 · arXiv (Cornell University)

Recent work has advocated for the use of deep learning to perform power allocation in the downlink of massive MIMO (maMIMO) networks. Yet, such deep learning models are vulnerable to adversarial attacks. In the context …

Preserving Sparsity and Privacy in Straggler-Resilient Distributed Matrix Computations

2023 · arXiv (Cornell University)

Existing approaches to distributed matrix computations involve allocating coded combinations of submatrices to worker nodes, to build resilience to stragglers and/or enhance privacy. In this study, we consider the challenge of preserving input sparsity in …