Search Results - "Non-i.i.d. data"

A systematic construction of non-i.i.d. data sets from a single data set: non-identically distributed data

Authors: Torra, Vicenç

Source: Knowledge and Information Systems. 65:991-1003

Subject Terms: Data sets, Federated learning, Machine learning, Non-i.i.d. data

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-201235
https://doi.org/10.1007/s10115-022-01785-3

Federated Learning in Heterogeneous Wireless Networks With Adaptive Mixing Aggregation and Computation Reduction

Authors: Jingxin Li Xiaolan Liu Toktam Mahmoodi

Source: IEEE Open Journal of the Communications Society, Vol 5, Pp 2164-2182 (2024)

Subject Terms: Load modeling, Data models, Federated learning, 0211 other engineering and technologies, Adaptation models, Computational modeling, non-I.I.D. data, Computation Efficiency, TK5101-6720, 02 engineering and technology, computation efficiency, Asynchronous Federated Learning, Performance evaluation, Telecommunication, 0202 electrical engineering, electronic engineering, information engineering, Training, Non-I.I.D. data, Federated Learning, Transportation and communications, asynchronous federated learning, HE1-9990

Access URL: https://doaj.org/article/395a393c4b4d40e1872a7332fd935044

AFAFed—Asynchronous Fair Adaptive Federated learning for IoT stream applications

Authors: Baccarelli E. Scarpiniti M. Momenzadeh A. et al.

Source: Computer Communications. 195:376-402

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Adaptive asynchronous FL, Distributed ML, Heterogeneous fog computing ecosystems, Non-i.i.d. data, Personalization-vs.-generalization trade-off

File Description: application/pdf

Access URL: https://hdl.handle.net/11573/1655821
https://doi.org/10.1016/j.comcom.2022.09.016

Federated SVHN (i.i.d.) and CIFAR-10 (i.i.d. and non-i.i.d.)

Authors: Lange, Lucas orcid:0000-0002-6745- Borchardt, Ole et al.

Subject Terms: SVHN, CIFAR-10, Federated Learning, i.i.d. data, non-i.i.d. data

Relation: https://www.cs.toronto.edu/~kriz/learning-features-2009-TR.pdf; https://research.google/pubs/reading-digits-in-natural-images-with-unsupervised-feature-learning/; arXiv:2501.17634; https://zenodo.org/records/14735130; oai:zenodo.org:14735130; https://doi.org/10.5281/zenodo.14735130

Availability: https://doi.org/10.5281/zenodo.14735130
https://zenodo.org/records/14735130

NETWORK-AWARE FEDERATED LEARNING ACROSS HIGHLY HETEROGENEOUS EDGE/FOG NETWORKS

Authors: Su Wang

Subject Terms: Networking and communications, Machine learning not elsewhere classified, Federated Learning, Semi-Supervised Learning, Unlabeled Data, Non-i.i.d. Data, Unbalanced Data, Resource Allocation, Wireless Edge Networks

Relation: https://figshare.com/articles/thesis/NETWORK-AWARE_FEDERATED_LEARNING_ACROSS_HIGHLY_HETEROGENEOUS_EDGE_FOG_NETWORKS/24757092

Availability: https://doi.org/10.25394/pgs.24757092.v1

On the ERM Principle With Networked Data

Authors: Wang, Yuanhong Wang, Yuyi Liu, Xingwu et al.

Source: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 32 No. 1 (2018): Thirty-Second AAAI Conference on Artificial Intelligence ; 2374-3468 ; 2159-5399

Subject Terms: Generalization error bounds, Non-i.i.d. data, U-statistics, Fully polynomial-time approximation scheme

File Description: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/11643/11502; https://ojs.aaai.org/index.php/AAAI/article/view/11643

Availability: https://ojs.aaai.org/index.php/AAAI/article/view/11643
https://doi.org/10.1609/aaai.v32i1.11643

NETWORK-AWARE FEDERATED LEARNING ACROSS HIGHLY HETEROGENEOUS EDGE/FOG NETWORKS

Authors: Su Wang (17592381)

Subject Terms: Networking and communications, Machine learning not elsewhere classified, Federated Learning, Semi-Supervised Learning, Unlabeled Data, Non-i.i.d. Data, Unbalanced Data, Resource Allocation, Wireless Edge Networks.

Relation: https://figshare.com/articles/thesis/NETWORK-AWARE_FEDERATED_LEARNING_ACROSS_HIGHLY_HETEROGENEOUS_EDGE_FOG_NETWORKS/24757092

Χρήση federated learning για τη συνεργατική ανίχνευση δικτυακών απειλών με υβριδικό μοντέλο βαθιάς μάθησης ; Using federated learning for the cooperative detection of network threats with a hybrid deep learning model

Authors: Μπίμπας, Ηλίας Bimpas, Ilias

Subject Terms: Σύστημα ανίχνευσης εισβολής, Βαθιά μάθηση, Υβριδικό μοντέλο, Ομοσπονδιακή μάθηση, Μη ανεξάρτητα και ταυτόσημα κατανεμημένα δεδομένα, Intrusion detection system, Deep learning, Hybrid model, Federated learning, Non-i.i.d. data

File Description: application/pdf

Relation: https://dspace.lib.ntua.gr/xmlui/handle/123456789/56074; http://dx.doi.org/10.26240/heal.ntua.23772

Availability: https://dspace.lib.ntua.gr/xmlui/handle/123456789/56074
https://doi.org/10.26240/heal.ntua.23772

Measurement-Efficient Quickest Change Detection in On-Off Models for Dynamic Spectrum Access

Authors: Lindståhl, Simon Proutiere, Alexandre Johnsson, Andreas

Subject Terms: Change point detection, sequential analysis, non-i.i.d. data, measurements, cognitive radio, dynamic spectrum access, Informations- och kommunikationsteknik, Information and Communication Technology, Optimeringslära och systemteori, Optimization and Systems Theory

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-360483

Analytical Study of Performance of Linear Discriminant Analysis in Stochastic Settings.

Authors: Zollanvari A Hua J Dougherty ER

Source: Pattern recognition [Pattern Recognit] 2013 Nov; Vol. 46 (11), pp. 3017-3029.

Publication Type: Journal Article

Journal Info: Publisher: Elsevier Country of Publication: England NLM ID: 0250655 Publication Model: Print Cited Medium: Print ISSN: 0031-3203 (Print) Linking ISSN: 00313203 NLM ISO Abbreviation: Pattern Recognit Subsets: PubMed not MEDLINE

Measurement-Efficient Quickest Change Detection in On-Off Models for Dynamic Spectrum Access

Authors: Lindståhl, Simon Proutiere, Alexandre Johnsson, Andreas

Index Terms: Change point detection, sequential analysis, non-i.i.d. data, measurements, cognitive radio, dynamic spectrum access, Communication Systems, Kommunikationssystem, Manuscript (preprint), info:eu-repo/semantics/preprint, text

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-360483