29 citations · 39 across the 6 of their papers we have counts for
8 papers
Safe Exploration for Nonlinear Processes Using Online Gaussian Process Learning
Stefano Tonini, Soroush Rastegarpour, Hamid Reza Feyzmahdavian +2
This paper proposes a safe data-driven control framework for nonlinear systems with partially known dynamics. The method ensures stability and constraint satisfaction during online…
Optimal convergence rates of totally asynchronous optimization
Xuyang Wu, Sindri Magnusson, Hamid Reza Feyzmahdavian +1
Asynchronous optimization algorithms are at the core of modern machine learning and resource allocation systems. However, most convergence results consider bounded information dela…
Delay-adaptive step-sizes for asynchronous learning
Xuyang Wu, Sindri Magnusson, Hamid Reza Feyzmahdavian +1
In scalable machine learning systems, model training is often parallelized over multiple nodes that run without tight synchronization. Most analysis results for the related asynchr…
Asynchronous Iterations in Optimization: New Sequence Results and Sharper Algorithmic Guarantees
Hamid Reza Feyzmahdavian, Mikael Johansson
We introduce novel convergence results for asynchronous iterations that appear in the analysis of parallel and distributed optimization algorithms. The results are simple to apply…
Advances in Asynchronous Parallel and Distributed Optimization
Mahmoud Assran, Arda Aytekin, Hamid Feyzmahdavian +2
Motivated by large-scale optimization problems arising in the context of machine learning, there have been several advances in the study of asynchronous parallel and distributed op…
Distributed learning with compressed gradients
Sarit Khirirat, Hamid Reza Feyzmahdavian, Mikael Johansson
Asynchronous computation and gradient compression have emerged as two key techniques for achieving scalability in distributed optimization for large-scale machine learning. This pa…