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1

A Scenario-Spatial Decomposition Approach With a Performance Guarantee for the Combined Bidding of Cascaded Hydropower and Renewables
Santosuosso, Luca ; Camal, Simon ; Lett, Arthur ; et al.
IEEE Transactions on Power Systems. :1-12

bidding strategy Energy storage Trustworthy bounds Wind power Energy markets Virtual power plant …
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2

ACCO: Accumulate While You Communicate for Communication-Overlapped Sharded LLM Training
Nabli, Adel ; Fournier, Louis ; Erbacher, Pierre ; et al.
The Thirty-ninth Annual Conference on Neural Information Processing Systems, Dec 2025, San diego (Californie), United States

San diego (Californie),... Communication Overlap Large Language Models Distributed Optimization [INFO.INFO-AI]Computer S... Artificial Intelligence... …
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3

Optimizing Network Performance: Distributed Load Balancing VNF Scaling in SDN-Based Cloud Infrastructures
Jianping, Zhang ; Li, Wei ; Sharma, Priya ; et al.

Software-Defined Network... Software-Defined Network... Virtual Network Function... Load Balancing Distributed Optimization ADMM …
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4

Sparsity-based regularization for learning over multitask graphs
Zgheib, Yara ; Antonini, Marc ; Nassif, Roula ; et al.

Edimbourg, United Kingdo... Distributed optimization multitask graph personalized learning non-smooth regularizatio... proximal operator …
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5

Multi-Market Bidding of Virtual Power Plants with Machine Learning-Assisted Asynchronous Distributed Optimization
Monroc, Claire, Bizon ; Stippel, Lukas ; Camal, Simon ; et al.

Asynchronous distributed... Communication Delays Virtual power plants Decision-focused learnin... Machine learning [MATH.MATH-OC]Mathematic... …
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6

Setwise Coordinate Descent for Dual Asynchronous Decentralized Optimization
Costantini, Marina ; Liakopoulos, Nikolaos ; Mertikopoulos, Panayotis ; et al.
IEEE Transactions on Automatic Control. :1-16

decentralized optimizati... distributed machine lear... distributed optimization multi-agent optimization optimization over networ... coordinate descent …
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7

Random Coordinate Descent for Resource Allocation in Open Multiagent Systems
Monnoyer de Galland, Charles ; Vizuete, Renato ; Hendrickx, Julien ; et al.
IEEE Transactions on Automatic Control. 69(11):7600-7613

Open multi-agent systems distributed optimization gradient methods agents and autonomous sy... [SPI]Engineering Science...
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8

Federated Learning under Heterogeneous and Correlated Client Availability
Rodio, Angelo ; Faticanti, Francescomaria ; Marfoq, Othmane ; et al.
IEEE INFOCOM 2023 - IEEE Conference on Computer Communications. :1-10

New York City, United St... Federated Learning Distributed Optimization [INFO.INFO-LG]Computer S... Machine Learning [cs.LG] [STAT.ML]Statistics [sta... …
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9

ADMM-Tracking Gradient for Distributed Optimization Over Asynchronous and Unreliable Networks
Guido Carnevale ; Nicola Bastianello ; Giuseppe Notarstefano ; et al.
IEEE Transactions on Automatic Control. 70:5160-5175

Optimization and Control... Optimization and Control FOS: Mathematics Cooperative control distributed optimization optimization …
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10

Predefined-time observer-based distributed consensus optimization control of nonlinear multi-agent systems
Guo, Lina ; He, Shuping ; Shi, Jiasheng ; et al.
Nonlinear Dynamics: An International Journal of Nonlinear Dynamics and Chaos in Engineering Systems. 113(24):33603-33622

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11

Deep Reinforcement Learning Based Distributed Optimization Framework for Optimal Power Flow in Multi-Region Power Systems
Zhou, Shuning
Journal of Electrical Engineering & Technology. 20(8):5591-5602

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12

Riemannian diffusion adaptation over graphs with application to online distributed PCA
Wang, Xiuheng ; Borsoi, Ricardo Augusto ; Richard, Cédric ; et al.
International Conference on Acoustics, Speech and Signal Processing, ICASSP 2024, Apr 2024, Séoul, South Korea. ⟨10.1109/ICASSP48485.2024.10446975⟩

Séoul, South Korea Diffusion strategy Riema... Diffusion strategy Riemannian manifolds distributed optimization multi-agent system …
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13

Resource allocation in open multi-agent systems: an online optimization analysis
Vizuete, Renato ; de Galland, Charles Monnoyer ; Hendrickx, Julien ; et al.
CDC 2022 - 61st IEEE Conference on Decision and Control. :5185-5191

Cancun, Mexico Agents and autonomous sy... Gradient methods Distributed optimization Open multi-agent systems [SPI.AUTO]Engineering Sc... …
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14

Delay-tolerant distributed Bregman proximal algorithms
Chraibi, Sélim ; Iutzeler, Franck ; Malick, Jérôme ; et al.
Optimization Methods and Software. :1-17

Distributed optimization Asynchronous methods Proximal algorithms Bregman divergence Poisson inverse problems [MATH.MATH-OC]Mathematic... …
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15

User-Centric Federated Learning
Mestoukirdi, Mohamad ; Zecchin, Matteo ; Gesbert, David ; et al.
GLOBECOM 2021. :1-6

Madrid, Spain Personalized federated l... Personalized federated l... distributed optimization user-centric aggregation statistical learning the... …
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16

Distributed optimization for IoT attack detection using federated learning and Siberian Tiger optimizer
Brij B. Gupta ; Akshat Gaurav ; Wadee Alhalabi ; et al.
ICT Express, Vol 11, Iss 3, Pp 542-546 (2025)

Siberian Tiger Optimizat... Federated learning IoT attack detection Information technology T58.5-58.64 CNN model …
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17

A Distributed Feedback-Based Framework for Nonlinear Aggregative Optimal Control
Lorenzo Sforni ; Guido Carnevale ; Giuseppe Notarstefano
IEEE Transactions on Automatic Control. 70:3784-3799

Optimal control, distrib...
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18

Parallel inexact Levenberg–Marquardt method for nearly-separable nonlinear least squares
Fodor, Lidija ; Jakovetić, Dušan ; Krejić, Nataša ; et al.
Journal of Global Optimization. 92:663-691

Distributed optimization Sparse nonlinear least s... Inexact Levenberg–Marqua... Nearly separable problem...
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19

Gradient descent for resource allocation with packet loss
Vizuete, Renato ; Frasca, Paolo ; Panteley, Elena ; et al.
NecSys 2022 - 9th IFAC Conference on Networked Systems. :109-114

Zurich, Switzerland Distributed optimization multi-agent systems packet loss gradient descent resource allocation …
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20

Auction-based and Distributed Optimization Approaches for Scheduling Observations in Satellite Constellations with Exclusive Orbit Portions
Picard, Gauthier ; DTIS, ONERA, Université de Toulouse [Toulouse] ; ONERA-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)
21st International Conference on Autonomous Agents and Multia-gent Systems (AAMAS 2022). :1056-1064

Online, New Zealand DISTRIBUTED OPTIMIZATION RESOURCE ALLOCATION SCHEDULING SATELLITE CONSTELLATIONS [INFO.INFO-MA]Computer S... …
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