Výsledky vyhľadávania - ML: Learning on the Edge & Model Compression

PrivaNet-FL: Enhancing Privacy and Minimizing Energy Overhead for Federated Learning System on Edge Devices.

Autori: Gowthami, D. Vigenesh, M.

Zdroj: Journal of Cybersecurity & Information Management; 2025, Vol. 16 Issue 2, p28-46, 19p

Predmety: DATA privacy, FEDERATED learning, FACE-to-face communication, REAL-time computing, ENERGY conservation

Intelligent Edge Computing and Machine Learning: A Survey of Optimization and Applications.

Autori: Cajas Ordóñez, Sebastián A. Samanta, Jaydeep Suárez-Cetrulo, Andrés L. a ďalší

Zdroj: Future Internet; Sep2025, Vol. 17 Issue 9, p417, 40p

Predmety: EDGE computing, MACHINE learning, SYSTEM of systems, SIGNAL quantization, DISTRIBUTED computing, MATHEMATICAL optimization

Developing Energy-Efficient Machine Learning Algorithms for Edge Devices

Autori: C. Jeyalakshmi S. Sajithabanu N.Thillainayagi a ďalší

Zdroj: Journal of Computer Science Engineering and Software Testing; Vol. 11 No. 2 (2025); 11-23; 2581-6969

Témy: Edge computing, Energy-efficient machine learning, Federated learning, Hardware-aware optimization, Knowledge distillation, Low-power AI, Model compression, Neural architecture search, Quantization, Real-time inference, info:eu-repo/semantics/article, info:eu-repo/semantics/publishedVersion, Peer-reviewed Article

URL: https://matjournals.net/engineering/index.php/JOCSES/article/view/1938
https://matjournals.net/engineering/index.php/JOCSES/article/view/1938/2698
https://matjournals.net/engineering/index.php/JOCSES/article/view/1938/2698

Edge Learning with Timeliness Constraints: Challenges and Solutions.

Autori: Sun, Yuxuan Shi, Wenqi Huang, Xiufeng a ďalší

Zdroj: IEEE Communications Magazine; Dec2020, Vol. 58 Issue 12, p27-33, 7p

Predmety: DATA compression, PRODUCTION scheduling, RESOURCE management, AUGMENTED reality, EDGES (Geometry)

A Comprehensive Review and a Taxonomy of Edge Machine Learning: Requirements, Paradigms, and Techniques.

Autori: Li, Wenbin Hacid, Hakim Almazrouei, Ebtesam a ďalší

Zdroj: AI; Sep2023, Vol. 4 Issue 3, p729-786, 58p

Predmety: MACHINE learning, ARTIFICIAL intelligence, SOFT computing, ELECTRONIC data processing, TAXONOMY, EDGE computing, DEEP learning

EPSD: Early Pruning with Self-Distillation for Efficient Model Compression

Autori: Chen, Dong Liu, Ning Zhu, Yichen a ďalší

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38 No. 10: AAAI-24 Technical Tracks 10; 11258-11266 ; 2374-3468 ; 2159-5399

Predmety: ML: Learning on the Edge & Model Compression, CV: Applications, CV: Learning & Optimization for CV, ML: Classification and Regression, ML: Deep Learning Algorithms, ML: Multi-class/Multi-label Learning & Extreme Classification, ML: Optimization

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/29004/29906; https://ojs.aaai.org/index.php/AAAI/article/view/29004

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/29004
https://doi.org/10.1609/aaai.v38i10.29004

Precision Unveiled in Unborn: A Cutting-Edge Hybrid Machine Learning Approach for Fetal Health State Classification.

Autori: Prachi Sabherwal, Pooja Agrawal, Monika a ďalší

Zdroj: Cardiovascular Engineering & Technology; Dec2025, Vol. 16 Issue 6, p641-662, 22p

An overview of artificial intelligence and machine learning in shoulder surgery.

Autori: Cho, Sung-Hyun Kim, Yang-Soo

Zdroj: Clinics in Shoulder & Elbow; Jun2025, Vol. 28 Issue 2, p242-250, 9p

Predmety: MACHINE learning, FEDERATED learning, ENSEMBLE learning, ARTIFICIAL intelligence, REINFORCEMENT learning

Lifelong Compression Mixture Model via Knowledge Relationship Graph

Autori: Ye, Fei Bors, Adrian G.

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 37 No. 9: AAAI-23 Technical Tracks 9; 10900-10908 ; 2374-3468 ; 2159-5399

Predmety: ML: Transfer, Domain Adaptation, Multi-Task Learning, ML: Graph-based Machine Learning, ML: Learning on the Edge & Model Compression, ML: Lifelong and Continual Learning

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/26292/26064; https://ojs.aaai.org/index.php/AAAI/article/view/26292

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/26292
https://doi.org/10.1609/aaai.v37i9.26292

Multi-Criterion Client Selection for Efficient Federated Learning

Autori: Tahir, Mehreen Ali, Muhammad Intizar

Zdroj: Proceedings of the AAAI Symposium Series; Vol. 3 No. 1: Proceedings of the 2024 AAAI Spring Symposium Series; 318-322 ; 2994-4317

Predmety: ML: Distributed Machine Learning & Federated Learning, ML: Optimization, ML: Learning On The Edge & Model Compression, ML: Evaluation And Analysis (Machine Learning)

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI-SS/article/view/31227/33387

Dostupnosť: https://ojs.aaai.org/index.php/AAAI-SS/article/view/31227
https://doi.org/10.1609/aaaiss.v3i1.31227

A Survey on Model Compression and Acceleration for Pretrained Language Models

Autori: Xu, Canwen McAuley, Julian

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 37 No. 9: AAAI-23 Technical Tracks 9; 10566-10575 ; 2374-3468 ; 2159-5399

Predmety: ML: Learning on the Edge & Model Compression, SNLP: Language Models

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/26255/26027; https://ojs.aaai.org/index.php/AAAI/article/view/26255

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/26255
https://doi.org/10.1609/aaai.v37i9.26255

RAVE-HD: A Novel Sequential Deep Learning Approach for Heart Disease Risk Prediction in e-Healthcare.

Autori: Khan, Muhammad Jaffar Raza, Basit Faheem, Muhammad

Zdroj: Diagnostics (2075-4418); Nov2025, Vol. 17 Issue 22, p2866, 50p

Predmety: HEART diseases, DEEP learning, MEDICAL screening, FEATURE selection, MACHINE learning, PREDICTION models, DIGITAL health, STATISTICAL bias

Complement Sparsification: Low-Overhead Model Pruning for Federated Learning

Autori: Jiang, Xiaopeng Borcea, Cristian

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 37 No. 7: AAAI-23 Technical Tracks 7; 8087-8095 ; 2374-3468 ; 2159-5399

Predmety: ML: Distributed Machine Learning & Federated Learning, ML: Learning on the Edge & Model Compression

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/25977/25749; https://ojs.aaai.org/index.php/AAAI/article/view/25977

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/25977
https://doi.org/10.1609/aaai.v37i7.25977

FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing

Autori: Jia, Yongzhe Zhang, Xuyun Beheshti, Amin a ďalší

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38 No. 11: AAAI-24 Technical Tracks 11; 12848-12856 ; 2374-3468 ; 2159-5399

Predmety: ML: Learning on the Edge & Model Compression, APP: Internet of Things, Sensor Networks & Smart Cities, ML: Transfer, Domain Adaptation, Multi-Task Learning, ML: Representation Learning

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/29181/30234; https://ojs.aaai.org/index.php/AAAI/article/view/29181/30235; https://ojs.aaai.org/index.php/AAAI/article/view/29181

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/29181
https://doi.org/10.1609/aaai.v38i11.29181

Predicting Axillary Lymph Node Metastasis in Breast Cancer Using Ultrasound and Machine Learning with SHAP.

Autori: Bai, Gengyan Zhong, Xiaohong Wu, Youping a ďalší

Zdroj: Cancer Management & Research; Sep2025, Vol. 17, p2183-2197, 15p

Predmety: BREAST cancer, MACHINE learning, PREDICTION models, LYMPHATIC metastasis, COMPUTER-assisted image analysis (Medicine), PROGNOSIS, BOOSTING algorithms

Geografický termín: XIAMEN Shi (China)

Generative Model-Based Feature Knowledge Distillation for Action Recognition

Autori: Wang, Guiqin Zhao, Peng Shi, Yanjiang a ďalší

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38 No. 14: AAAI-24 Technical Tracks 14; 15474-15482 ; 2374-3468 ; 2159-5399

Predmety: ML: Learning on the Edge & Model Compression, CV: Applications, CV: Other Foundations of Computer Vision, CV: Video Understanding & Activity Analysis, KRR: Applications, ML: Applications

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/29473/30776; https://ojs.aaai.org/index.php/AAAI/article/view/29473/30777; https://ojs.aaai.org/index.php/AAAI/article/view/29473

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/29473
https://doi.org/10.1609/aaai.v38i14.29473

OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models

Autori: Lee, Changhun Jin, Jungyu Kim, Taesu a ďalší

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38 No. 12: AAAI-24 Technical Tracks 12; 13355-13364 ; 2374-3468 ; 2159-5399

Predmety: ML: Learning on the Edge & Model Compression, NLP: (Large) Language Models, NLP: Learning & Optimization for NLP

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/29237/30335; https://ojs.aaai.org/index.php/AAAI/article/view/29237/30336; https://ojs.aaai.org/index.php/AAAI/article/view/29237

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/29237
https://doi.org/10.1609/aaai.v38i12.29237

Sustainable E-Health: Energy-Efficient Tiny AI for Epileptic Seizure Detection via EEG.

Autori: Hizem, Moez Aoueileyine, Mohamed Ould-Elhassen Belhaouari, Samir Brahim a ďalší

Zdroj: Biomedical Engineering & Computational Biology; 8/10/2025, p1-13, 13p

Predmety: ELECTROENCEPHALOGRAPHY, SEIZURES (Medicine), MEDICAL innovations, REAL-time computing, DIGITAL health, MACHINE learning, INTERNET of things

ConsistentEE: A Consistent and Hardness-Guided Early Exiting Method for Accelerating Language Models Inference

Autori: Zeng, Ziqian Hong, Yihuai Dai, Hongliang a ďalší

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38 No. 17: AAAI-24 Technical Tracks 17; 19506-19514 ; 2374-3468 ; 2159-5399

Predmety: NLP: (Large) Language Models, ML: Learning on the Edge & Model Compression

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/29922/31612; https://ojs.aaai.org/index.php/AAAI/article/view/29922

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/29922
https://doi.org/10.1609/aaai.v38i17.29922

Fluctuation-Based Adaptive Structured Pruning for Large Language Models

Autori: An, Yongqi Zhao, Xu Yu, Tao a ďalší

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38 No. 10: AAAI-24 Technical Tracks 10; 10865-10873 ; 2374-3468 ; 2159-5399

Predmety: ML: Learning on the Edge & Model Compression, NLP: (Large) Language Models

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/28960/29826; https://ojs.aaai.org/index.php/AAAI/article/view/28960/29827; https://ojs.aaai.org/index.php/AAAI/article/view/28960

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/28960
https://doi.org/10.1609/aaai.v38i10.28960