A variance‐reduced distributed stochastic momentum algorithm over directed networks
Sign Up to like & getrecommendations! Published in 2025 at "Asian Journal of Control"
DOI: 10.1002/asjc.3775
Abstract: The distributed optimization to minimize a smooth and strongly convex function is considered, in which the function can be described as the finite sum of all local objective functions over directed networks. A variance‐reduced distributed… read more here.
Keywords: variance; momentum; reduced distributed; directed networks ... See more keywords
Distributed Stochastic Search Algorithm for Multi-ship Encounter Situations
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Navigation"
DOI: 10.1017/s037346331700008x
Abstract: Ship collision avoidance involves helping ships find routes that will best enable them to avoid a collision. When more than two ships encounter each other, the procedure becomes more complex since a slight change in… read more here.
Keywords: stochastic search; search; distributed stochastic; search algorithm ... See more keywords
Fingerprints of Element Concentrations in Infective Endocarditis Obtained by Mass Spectrometric Imaging and t-Distributed Stochastic Neighbor Embedding.
Sign Up to like & getrecommendations! Published in 2022 at "ACS infectious diseases"
DOI: 10.1021/acsinfecdis.1c00485
Abstract: Staphylococcus aureus-induced infective endocarditis (IE) is a life-threatening disease. Differences in virulence between distinct S. aureus strains, which are partly based on the molecular mechanisms during bacterial adhesion, are not fully understood. Yet, distinct molecular… read more here.
Keywords: infective endocarditis; tissue; mass; stochastic neighbor ... See more keywords
Zeroth-Order Distributed Stochastic Optimization Over Riemannian Manifolds
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2025.3620779
Abstract: Due to its ability to handle strict constraints on feasible domains, distributed optimization over a Riemannian manifold offers an attractive solution for many practical applications. To develop such an algorithm for scenarios where the explicit… read more here.
Keywords: zeroth order; order distributed; optimization riemannian; distributed stochastic ... See more keywords
Distributed Stochastic Approximation Algorithm With Expanding Truncations
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Automatic Control"
DOI: 10.1109/tac.2019.2912713
Abstract: In this paper, a novel distributed stochastic approximation algorithm (DSAA) is proposed to seek roots of the sum of local functions, each of which is associated with an agent from multiple agents connected over a… read more here.
Keywords: expanding truncations; local functions; stochastic approximation; approximation algorithm ... See more keywords
Convergence in High Probability of Distributed Stochastic Gradient Descent Algorithms
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Automatic Control"
DOI: 10.1109/tac.2023.3327319
Abstract: In this article, the problem of distributed optimization with nonconvex objective functions is studied by employing a network of agents. Each agent only has access to a noisy estimate on the gradient of its own… read more here.
Keywords: probability; distributed stochastic; gradient; high probability ... See more keywords
Accelerated Distributed Stochastic Nonconvex Optimization Over Time-Varying Directed Networks
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Automatic Control"
DOI: 10.1109/tac.2024.3479888
Abstract: Distributed stochastic nonconvex optimization problems have recently received attention due to the growing interest of signal processing, computer vision, and natural language processing communities in applications deployed over distributed learning systems (e.g., federated learning). We… read more here.
Keywords: distributed stochastic; stochastic nonconvex; time varying; nonconvex optimization ... See more keywords
Byzantine-Robust Distributed Stochastic Nonconvex Optimization in Adversarial Environments Over Unbalanced Networks
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Automatic Control"
DOI: 10.1109/tac.2025.3579218
Abstract: In this article, we focused on a Byzantine-robust distributed stochastic nonconvex optimization problem with smooth local cost functions over unbalanced networks. In particular, the nodes in a network are to find a stationary solution minimizing… read more here.
Keywords: unbalanced networks; robust distributed; byzantine robust; distributed stochastic ... See more keywords
A Flexible Distributed Stochastic Optimization Framework for Concurrent Tasks in Processing Networks
Sign Up to like & getrecommendations! Published in 2021 at "IEEE/ACM Transactions on Networking"
DOI: 10.1109/tnet.2021.3078054
Abstract: Distributed stochastic optimization has important applications in the practical implementation of machine learning and signal processing setup by providing means to allow interconnected network of processors to work towards the optimization of a global objective… read more here.
Keywords: optimization; flexible distributed; concurrent tasks; stochastic optimization ... See more keywords
Distributed Stochastic MPC for Networked Linear Systems With a Multirate Sampling Mechanism
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2020.3048998
Abstract: In this article, a distributed stochastic model predictive control (MPC) algorithm with a multirate sampling mechanism is proposed for a networked linear system with multiple dynamic subsystems. A delta operator approach is used for the… read more here.
Keywords: stochastic mpc; sampling mechanism; multirate sampling; distributed stochastic ... See more keywords
On the Use of t-Distributed Stochastic Neighbor Embedding for Data Visualization and Classification of Individuals with Parkinson's Disease
Sign Up to like & getrecommendations! Published in 2018 at "Computational and Mathematical Methods in Medicine"
DOI: 10.1155/2018/8019232
Abstract: Parkinson's disease (PD) is a neurodegenerative disorder that remains incurable. The available treatments for the disorder include pharmacologic therapies and deep brain stimulation (DBS). These approaches may cause distinct side effects and motor responses. This… read more here.
Keywords: classification; neighbor embedding; distributed stochastic; data visualization ... See more keywords