312 citations · 381 across the 17 of their papers we have counts for
5 papers · 1 filter
Federated Hyperdimensional Computing for Resource-Constrained Industrial IoT
Nikita Zeulin, Olga Galinina, Nageen Himayat +1
In the Industrial Internet of Things (IIoT) systems, edge devices often operate under strict constraints in memory, compute capability, and wireless bandwidth. These limitations ch…
Large-Margin Hyperdimensional Computing: A Learning-Theoretical Perspective
Nikita Zeulin, Olga Galinina, Ravikumar Balakrishnan +2
Overparameterized machine learning (ML) methods such as neural networks may be prohibitively resource intensive for devices with limited computational capabilities. Hyperdimensiona…
Resource-Efficient Federated Hyperdimensional Computing
Nikita Zeulin, Olga Galinina, Nageen Himayat +1
In conventional federated hyperdimensional computing (HDC), training larger models usually results in higher predictive performance but also requires more computational, communicat…
Multi-Task Model Personalization for Federated Supervised SVM in Heterogeneous Networks
Aleksei Ponomarenko-Timofeev, Olga Galinina, Ravikumar Balakrishnan +3
Federated systems enable collaborative training on highly heterogeneous data through model personalization, which can be facilitated by employing multi-task learning algorithms. Ho…
Dynamic Network-Assisted D2D-Aided Coded Distributed Learning
Nikita Zeulin, Olga Galinina, Nageen Himayat +2
Today, various machine learning (ML) applications offer continuous data processing and real-time data analytics at the edge of a wireless network. Distributed real-time ML solution…