Results 131 to 140 of about 1,993,316 (300)

Quarterly report of the Client Security Fund Committee. 2015: Oct.-Dec. [PDF]

, 2015
Quarterly; Began in 2005?; "Pursuant to Practice Book [section] 2-72(e), the following is a report of the activities of the Client Security Fund Committee for ...
Connecticut. Client Security Fund Committee.
core  

Federated learning energy saving through client selection [PDF]

Contemporary applications leverage machine learning models to optimize performance, often necessitating data transmission to a remote server for training. However, this approach entails significant resource consumption.
Bittencourt, Luiz F., de Souza, Allan M., Maciel, Filipe, Braun, Torsten, Villas, Leandro A.   +4 more
core   +1 more source

Personalized Federated Learning with Attention-Based Client Selection

ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Personalized Federated Learning (PFL) relies on collective data knowledge to build customized models. However, non-IID data between clients poses significant challenges, as collaborating with clients who have diverse data distributions can harm local model performance, especially with limited training data.
Zihan Chen 0002, Jundong Li, Cong Shen 0001   +2 more
openaire   +2 more sources

Automated generative process synthesis via transformer‐based dual‐loop simulation and optimization

AIChE Journal, EarlyView.
Abstract This study presents a novel framework for automated generative process synthesis, addressing the complexity of simultaneously optimizing discrete topologies and continuous operating variables. To overcome conventional superstructure limitations, we propose a dual‐loop architecture integrating generative transformers with rigorous process ...
Yeong Woo Son, Chan Kim, Ji Hun Pak, Hain Lee, Jong Min Lee   +4 more
wiley   +1 more source

Client versus consultant influence on client involvement in computer system selection projects: a two-actor model of the theory of planned behavior [PDF]

, 2001
The engagement of external IS professionals to supplement in-house resources is a widespread and growing practice. Limited prior research on consultant engagement suggests client involvement is a key factor of success.
Gable, Guy, Chin, Wynne, Gable, Guy G., Chin, Wynne W.   +3 more
core   +2 more sources

Asynchronous Wireless Federated Learning With Probabilistic Client Selection

IEEE Transactions on Wireless Communications
To appear in IEEE Transactions on Wireless ...
Jiarong Yang, Yuan Liu, Fangjiong Chen, Wen Chen, Changle Li   +4 more
openaire   +2 more sources

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

FREQSEL: A Frequency-Based Method for Client Selection in Federated Learning

IEEE Access
Federated learning (FL) is a machine learning approach that allows multiple devices to collaborate in constructing a shared prediction model while keeping their sensitive data decentralized, avoiding the need for transmission to a central server. In each
Mohamed M'Haouach, Anass Houdou, Hamza Alami, Houda Bouraqqadi, Khalid Fardousse   +4 more
doaj   +1 more source

‘Are there causes and clients lawyers should not represent?’ Debates about client selection

Legal Ethics
Are There Causes and Clients Lawyers Should Not Represent?’ This Special Issue centres around a paper Richard L. Abel first presented at a session of the Working Group for Comparative Studies of Legal Professions meeting in Coimbra, Portugal in July 2022, in which he asks and addresses this question.
Tamara Butter, Trevor Clark
openaire   +2 more sources

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

Advanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury, Sebastian Gratz‐Kelly, Eric Wagner, Paul Motzki, Martina Lehser   +4 more
wiley   +1 more source