On the public citation graph

Secure and efficient parameters aggregation protocol for federated incremental learning and its applications

https://doi.org/10.1002/int.22727
0 signed · 37 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/dac.4179openalex-snapshot
Health care service delivery based on the Internet of things: A systematic and comprehensive study
inferredcites →https://doi.org/10.1002/int.22508openalex-snapshot
An effective framework for semistructured document classification via hierarchical attention model
inferredcites →https://doi.org/10.1002/int.22510openalex-snapshot
Advanced evasion attacks and mitigations on practical ML‐based phishing website classifiers
inferredcites →https://doi.org/10.1002/int.22519openalex-snapshot
Hysteresis compensation and adaptive control based evolutionary neural networks for piezoelectric actuator
inferredcites →https://doi.org/10.1002/int.22525openalex-snapshot
Integration of logistic regression and multilayer perceptron for intelligent single and dual axis solar tracking systems
inferredcites →https://doi.org/10.1002/wics.101openalex-snapshot
Principal component analysis
inferredcites →https://doi.org/10.1007/978-3-030-01219-9_9openalex-snapshot
Memory Aware Synapses: Learning What (not) to Forget
inferredcites →https://doi.org/10.1007/978-3-319-94478-4_19openalex-snapshot
Blockchain-Based Research Data Sharing Framework for Incentivizing the Data Owners
inferredcites →https://doi.org/10.1007/978-3-642-35289-8_25openalex-snapshot
Stochastic Gradient Descent Tricks
inferredcites →https://doi.org/10.1016/j.ins.2020.02.037openalex-snapshot
A training-integrity privacy-preserving federated learning scheme with trusted execution environment
inferredcites →https://doi.org/10.1017/cbo9781107298019openalex-snapshot
Understanding Machine Learning
inferredcites →https://doi.org/10.1038/s42256-019-0080-xopenalex-snapshot
Continual learning of context-dependent processing in neural networks
inferredcites →https://doi.org/10.1073/pnas.1611835114openalex-snapshot
Overcoming catastrophic forgetting in neural networks
inferredcites →https://doi.org/10.1109/iccv.2019.00040openalex-snapshot
Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild
inferredcites →https://doi.org/10.1109/icdcs42985.2018openalex-snapshot
2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)
inferredcites →https://doi.org/10.1109/icsiot47925.2019.00025openalex-snapshot
Securing Medical IoT Devices Using Diffie-Hellman and DES Cryptographic Schemes
inferredcites →https://doi.org/10.1109/iwqos.2018.8624183openalex-snapshot
Improved Adam Optimizer for Deep Neural Networks
inferredcites →https://doi.org/10.1109/rbme.2020.3013489openalex-snapshot
Secure and Robust Machine Learning for Healthcare: A Survey
inferredcites →https://doi.org/10.1109/tensymp50017.2020.9230731openalex-snapshot
Efficient Approach to Detect Epileptic Seizure using Machine Learning Models for Modern Healthcare System
inferredcites →https://doi.org/10.1109/tifs.2020.2988575openalex-snapshot
Federated Learning With Differential Privacy: Algorithms and Performance Analysis
inferredcites →https://doi.org/10.1109/tnnls.2019.2953131openalex-snapshot
Communication-Efficient Federated Deep Learning With Layerwise Asynchronous Model Update and Temporally Weighted Aggregation
inferredcites →https://doi.org/10.1109/tnsm.2021.3052223openalex-snapshot
APPM: Adaptive Parallel Processing Mechanism for Service Function Chains
inferredcites →https://doi.org/10.1109/tpds.2020.3043768openalex-snapshot
On the Effective Parallelization and Near-Optimal Deployment of Service Function Chains
inferredcites →https://doi.org/10.1109/wf-iot.2015.7389141openalex-snapshot
Secure end-to-end communication for constrained devices in IoT-enabled Ambient Assisted Living systems
inferredcites →https://doi.org/10.1631/fitee.1700813openalex-snapshot
Artificial intelligence and statistics

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4683585openalex-extracted
inferred← citeshttps://doi.org/10.1002/int.22794openalex-snapshot
Mining high utility pattern with negative items in dynamic databases
inferred← citeshttps://doi.org/10.1002/int.22884openalex-snapshot
Forward privacy multikeyword ranked search over encrypted database
inferred← citeshttps://doi.org/10.1002/int.22951openalex-snapshot
Decentralized federated meta‐learning framework for few‐shot multitask learning
inferred← citeshttps://doi.org/10.1002/int.22997openalex-snapshot
An effective and practical gradient inversion attack
inferred← citeshttps://doi.org/10.1016/j.csi.2022.103699openalex-snapshot
Energy trading scheme based on consortium blockchain and game theory
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.130844openalex-snapshot
Federated continual learning: Concepts, challenges, and solutions
inferred← citeshttps://doi.org/10.1016/j.patcog.2024.111048openalex-snapshot
Federated Incremental Learning algorithm based on Topological Data Analysis
inferred← citeshttps://doi.org/10.1109/tnnls.2023.3238724openalex-snapshot
An Efficient Federated Learning Framework for Machinery Fault Diagnosis With Improved Model Aggregation and Local Model Training
inferred← citeshttps://doi.org/10.3390/electronics12224633openalex-snapshot
FLIBD: A Federated Learning-Based IoT Big Data Management Approach for Privacy-Preserving over Apache Spark with FATE
inferred← citeshttps://doi.org/10.3390/ijerph20156539openalex-snapshot
A Review of Privacy Enhancement Methods for Federated Learning in Healthcare Systems
inferred← citeshttps://doi.org/10.3390/s22093445openalex-snapshot
A Universal Detection Method for Adversarial Examples and Fake Images
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.