General information metrics for improving AI model training efficiency
Sign Up to like & getrecommendations! Published in 2025 at "Artificial Intelligence Review"
DOI: 10.1007/s10462-025-11281-z
Abstract: To address the growing size of AI model training data and the lack of a universal data selection methodology–factors that significantly drive up training costs–this paper presents the General Information Metrics Evaluation (GIME) method. GIME… read more here.
Keywords: training; general information; information metrics; model ... See more keywords
A dynamic model of training transfer
Sign Up to like & getrecommendations! Published in 2019 at "Human Resource Management Review"
DOI: 10.1016/j.hrmr.2017.11.004
Abstract: Abstract We expand our understanding of the training transfer process by developing the Dynamic Transfer Model (DTM). We develop and examine linkages between intentions to transfer, the initial attempts to utilize training, and the integration… read more here.
Keywords: dynamic model; training; transfer; model training ... See more keywords
Efficient dataset generation for machine learning halide perovskite alloys
Sign Up to like & getrecommendations! Published in 2025 at "Physical Review Materials"
DOI: 10.1103/physrevmaterials.9.053802
Abstract: Lead-based perovskite solar cells have reached high efficiencies, but toxicity and lack of stability hinder their wide-scale adoption. These issues have been partially addressed through compositional engineering of perovskite materials, but the vast complexity of… read more here.
Keywords: efficient dataset; machine; machine learning; model training ... See more keywords
Data Collection Algorithms for Model Training in Internet of Vehicles
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DOI: 10.1109/jiot.2023.3299308
Abstract: In Internet of Vehicles (IoV), it is critical to collect sufficient data for model training, to support vehicular intelligent applications. However, the environment of IoV is highly dynamic due to the mobility of vehicles, making… read more here.
Keywords: data collection; iterative algorithm; internet vehicles; model ... See more keywords
Revisiting Dead Leaves Model: Training With Synthetic Data
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2021.3132289
Abstract: Deep neural networks targeting stereo disparity estimation have recently surpassed the performance of hand-crafted traditional models. However, training these networks require large labeled databases for obtaining accurate disparity estimates. In this letter, we address the… read more here.
Keywords: revisiting dead; leaves model; synthetic data; dead leaves ... See more keywords
ARASEC: Adaptive Resource Allocation and Model Training for Serverless Edge–Cloud Computing
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Internet Computing"
DOI: 10.1109/mic.2024.3514670
Abstract: Developing and deploying resource-aware artificial intelligence (AI) models presents a compelling optimization challenge in edge computing and serverless domains. Current research focuses mainly on scalable training and inference that uses serverless frameworks to optimize operational… read more here.
Keywords: edge cloud; resource; edge; model ... See more keywords
Cross-Dataset Model Training for Hyperspectral Image Classification Using Self-Supervised Learning
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2024.3493969
Abstract: With the development of deep learning and the increase in the amount of data, general artificial intelligence models have become a popular research area nowadays. When facing a new application scenario, a pretraining general model… read more here.
Keywords: classification; model training; hyperspectral image; self supervised ... See more keywords
A Self-Adaptive Bell–LaPadula Model Based on Model Training With Historical Access Logs
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2018.2807793
Abstract: In currently popular access control models, the security policies and regulations never change in the running system process once they are identified, which makes it possible for attackers to find the vulnerabilities in a system,… read more here.
Keywords: model based; system; bell lapadula; model ... See more keywords
Eiffel: Efficient and Fair Scheduling in Adaptive Federated Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Parallel and Distributed Systems"
DOI: 10.1109/tpds.2022.3187365
Abstract: Emerging machine learning (ML) technologies, in combination with the increasing computational power of mobile devices, lead to the extensive adoption of ML-based applications. Different from conventional model training that needs to collect all the user… read more here.
Keywords: federated learning; efficient fair; eiffel efficient; model training ... See more keywords
AtRec: Accelerating Recommendation Model Training on CPUs
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DOI: 10.1109/tpds.2024.3381186
Abstract: The popularity of recommendation models and the enhanced AI processing capability of CPUs have provided massive performance opportunities to deliver satisfactory experiences to a large number of users. Unfortunately, existing recommendation model training methods fail… read more here.
Keywords: recommendation model; level; atrec; recommendation ... See more keywords
Evaluation of Process Communication Model training for surgeons and other healthcare professionals: a survey
Sign Up to like & getrecommendations! Published in 2021 at "Anz Journal of Surgery"
DOI: 10.1111/ans.16351
Abstract: J. Med. 1987; 317: 141–5. 13. van der Graaf R, van Delden JJ. Equipoise should be amended, not abandoned. Clin. Trials 2011; 8: 408–16. 14. Johnson N, Lilford RJ, Brazier W. At what level of… read more here.
Keywords: process communication; training surgeons; evaluation process; process ... See more keywords