Fast spin‐echo approach for accelerated B1 gradient–based MRI
Sign Up to like & getrecommendations! Published in 2023 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.29592
Abstract: To expand on the previously developed B1+$$ {\mathrm{B}}_1^{+} $$ ‐encoding technique, frequency‐modulated Rabi‐encoded echoes (FREE), to perform accelerated image acquisition by collecting multiple lines of k‐space in an echo train. read more here.
Keywords: spin echo; accelerated gradient; echo approach; approach accelerated ... See more keywords
Accelerated gradient sliding for structured convex optimization
Sign Up to like & getrecommendations! Published in 2022 at "Computational Optimization and Applications"
DOI: 10.1007/s10589-022-00365-z
Abstract: Our main goal in this paper is to show that one can skip gradient computations for gradient descent type methods applied to certain structured convex programming (CP) problems. To this end, we first present an… read more here.
Keywords: optimization; structured convex; accelerated gradient; gradient sliding ... See more keywords
Accelerated gradient boosting
Sign Up to like & getrecommendations! Published in 2019 at "Machine Learning"
DOI: 10.1007/s10994-019-05787-1
Abstract: Gradient tree boosting is a prediction algorithm that sequentially produces a model in the form of linear combinations of decision trees, by solving an infinite-dimensional optimization problem. We combine gradient boosting and Nesterov’s accelerated descent… read more here.
Keywords: gradient boosting; accelerated gradient;
Accelerated Gradient Flow for Directed Graphs With Event-Based Broadcasting
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Control of Network Systems"
DOI: 10.1109/tcns.2023.3290112
Abstract: Accelerated gradients algorithms are currently at the receiving end of widespread interest in optimization theory, both under discrete- and continuous-time (CT) frameworks. In light of recent developments, in the first part of our work, we… read more here.
Keywords: gradient flow; directed graphs; based broadcasting; event ... See more keywords
Rapid Transitions With Robust Accelerated Delayed-Self-Reinforcement for Consensus-Based Networks
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Control Systems Technology"
DOI: 10.1109/tcst.2020.3032853
Abstract: Rapid transitions are important for the quick response of consensus-based, multi-agent networks to external stimuli. While high-gain can increase response speed, potential instability tends to limit the maximum possible gain, and therefore, limits the maximum… read more here.
Keywords: consensus based; consensus; accelerated delayed; rapid transitions ... See more keywords
Accelerated Gradient Approach For Deep Neural Network-Based Adaptive Control of Unknown Nonlinear Systems
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2024.3395064
Abstract: Recent connections in the adaptive control literature to continuous-time analogs of Nesterov’s accelerated gradient method have led to the development of new real-time adaptation laws based on accelerated gradient methods. However, previous results assume that… read more here.
Keywords: nonlinear systems; network based; control; adaptive control ... See more keywords
Nesterov Accelerated Gradient Tracking With Adam for Distributed Online Optimization.
Sign Up to like & getrecommendations! Published in 2025 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2025.3604059
Abstract: This article presents an accelerated distributed optimization algorithm for online optimization problems over large-scale networks. The proposed algorithm’s iteration only relies on local computation and communication. To effectively adapt to dynamic changes and achieve a… read more here.
Keywords: distributed online; online optimization; nesterov accelerated; dynamic regret ... See more keywords
The strength of Nesterov’s accelerated gradient in boosting transferability of stealthy adversarial attacks
Sign Up to like & getrecommendations! Published in 2025 at "PLOS One"
DOI: 10.1371/journal.pone.0337463
Abstract: Deep neural networks have been shown to be highly vulnerable to adversarial examples—inputs crafted to mislead models by adding subtle, human-imperceptible perturbations. Transferability and stealthiness are two crucial metrics for evaluating adversarial attacks. However, these… read more here.
Keywords: black box; transferability; boosting transferability; accelerated gradient ... See more keywords
Hybrid Modified Accelerated Gradient Method for Optimization Processes
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DOI: 10.3390/math12050632
Abstract: This research reveals a hybrid variant of the modified accelerated gradient method. We prove that derived iteration is linearly convergent on the set of uniformly convex functions. Performance profiles of the introduced hybrid method were… read more here.
Keywords: hybrid modified; method; gradient method; modified accelerated ... See more keywords