27 citations · 129 across the 27 of their papers we have counts for
8 papers · 1 filter
Partial Model Sharing Improves Byzantine Resilience in Federated Conformal Prediction
Ehsan Lari, Reza Arablouei, Stefan Werner
We propose a Byzantine-resilient federated conformal prediction (FCP) method that leverages partial model sharing, where only a subset of model parameters is exchanged each round.…
SA-PEF: Step-Ahead Partial Error Feedback for Efficient Federated Learning
Dawit Kiros Redie, Reza Arablouei, Stefan Werner
Biased gradient compression with error feedback (EF) reduces communication in federated learning (FL), but under non-IID data, the residual error can decay slowly, causing gradient…
Noise-Robust and Resource-Efficient ADMM-based Federated Learning
Ehsan Lari, Reza Arablouei, Vinay Chakravarthi Gogineni +1
Federated learning (FL) leverages client-server communications to train global models on decentralized data. However, communication noise or errors can impair model accuracy. To ad…
Resilience in Online Federated Learning: Mitigating Model-Poisoning Attacks via Partial Sharing
Ehsan Lari, Reza Arablouei, Vinay Chakravarthi Gogineni +1
Federated learning (FL) allows training machine learning models on distributed data without compromising privacy. However, FL is vulnerable to model-poisoning attacks where malicio…
In-situ animal behavior classification using knowledge distillation and fixed-point quantization
Reza Arablouei, Liang Wang, Caitlin Phillips +3
We explore the use of knowledge distillation (KD) for learning compact and accurate models that enable classification of animal behavior from accelerometry data on wearable devices…
Multimodal sensor data fusion for in-situ classification of animal behavior using accelerometry and GNSS data
Reza Arablouei, Ziwei Wang, Greg J. Bishop-Hurley +1
In this paper, we examine the use of data from multiple sensing modes, i.e., accelerometry and global navigation satellite system (GNSS), for classifying animal behavior. We extrac…