Aleksandar Armacki

Orcid: 0000-0001-7916-585X

According to our database1, Aleksandar Armacki authored at least 14 papers between 2019 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Optimal High-probability Convergence of Nonlinear SGD under Heavy-tailed Noise via Symmetrization.
CoRR, July, 2025

Distributed Center-Based Clustering: A Unified Framework.
IEEE Trans. Signal Process., 2025

High-probability Convergence Bounds for Online Nonlinear Stochastic Gradient Descent under Heavy-tailed Noise.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024
A One-Shot Framework for Distributed Clustered Learning in Heterogeneous Environments.
IEEE Trans. Signal Process., 2024

Large Deviations and Improved Mean-squared Error Rates of Nonlinear SGD: Heavy-tailed Noise and Power of Symmetry.
CoRR, 2024

Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: A Unified Framework and High-probability Guarantees.
CoRR, 2024

A Unified Framework for Gradient-based Clustering of Distributed Data.
CoRR, 2024

Distributed Gradient Clustering: Convergence and the Effect of Initialization.
Proceedings of the 58th Asilomar Conference on Signals, 2024

2023
High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise.
CoRR, 2023

Communication Efficient Model-Aware Federated Learning for Visual Crowd Counting and Density Estimation in Smart Cities.
Proceedings of the 31st European Signal Processing Conference, 2023

2022
One-Shot Federated Learning for Model Clustering and Learning in Heterogeneous Environments.
CoRR, 2022

Personalized Federated Learning via Convex Clustering.
Proceedings of the IEEE International Smart Cities Conference, 2022

Gradient Based Clustering.
Proceedings of the International Conference on Machine Learning, 2022

2019
Distributed Trust-Region Method With First Order Models.
Proceedings of the IEEE EUROCON 2019, 2019


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