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• Dynamic Pricing for Revenue Management in Health and Hospitality Industry with Federated Learning
  crossref H.M. Moyeenudin, Jaisree Anand, R. Anandan 2026-05-08T21:41:08Z 置信度 0.70
• Inference Attacks and Counterattacks in Federated Learning
  crossref Shui Yu, Lei Cui 2023-03-26T21:30:41Z 置信度 0.70
• Secure Multi-party Computation in Federated Learning
  crossref Shui Yu, Lei Cui 2023-03-26T21:30:41Z 置信度 0.70
• Protecting Against Data Leakage in Federated Learning: What Approach Should You Choose?
  crossref Nathalie Baracaldo, Runhua Xu 2022-07-07T12:16:52Z 置信度 0.70
• Towards Model-Agnostic Federated Learning over Networks
  We present a model-agnostic federated learning method for decentralized data with an intrinsic network structure.The network structure reflects similarities between the (statistics of) local datasets and, in turn, their associated local models. Our method is a…
  crossref Alexander Jung 2023-02-15T10:53:14Z 置信度 0.70
• Intrinsic Gradient Compression for Scalable and Efficient Federated Learning
  crossref Luke Melas-Kyriazi, Franklyn Wang 2022-06-03T01:34:53Z 置信度 0.70
• Optimizing federated learning with heterogeneous and unreliable clients
  crossref Yuchang Sun 2024-10-17T01:55:46Z 置信度 0.70
• Blockchain–Integrated Federated Learning Arcitectures for Trustworthy and Privacy–Preserving IoT Security
  crossref MUTHUPANDI G, Nandhakumar R, Vishnu B, SIVAKUMAR G 2026-05-03T20:52:58Z 置信度 0.70
• Federated Learning for Collaborative Financial Crimes Detection
  crossref Toyotaro Suzumura, Yi Zhou, Ryo Kawahara, Nathalie Baracaldo 等 2022-07-07T12:16:52Z 置信度 0.70
• Figure 2: Federated learning payment processing for bitcoin’s timing commitments.
  crossref 2026-02-04T08:57:09Z 置信度 0.70
• Differentially Private Wireless Federated Learning
  crossref 2022-06-16T00:05:40Z 置信度 0.70
• Minimum exposure approach for trustworthy vertical federated learning
  crossref Dashan Gao 2025-06-17T01:00:06Z 置信度 0.70
• Enhancing Federated Learning for Financial Sector via Graph Learning and Language Models
  Amélioration de l'Apprentissage Fédéré pour le Secteur Financier via l'Apprentissage par Graphes et les Modèles de Langage Dans le secteur financier moderne, la nécessité de modèles d'apprentissage automatique robustes devient de plus en plus cruciale, mais le…
  crossref Farouk Damoun 2026-04-08T20:44:48Z 置信度 0.70
• Predictive maintenance for vessel machinery using federated learning
  Η προγνωστική συντήρηση στη ναυτιλία υποστηρίζεται ολοένα και περισσότερο από μοντέλα που εκπαιδεύονται σε ροές δεδομένων υψηλής συχνότητας από αισθητήρες πλοίων. Ωστόσο, οι περισσότερες υφιστάμενες προσεγγίσεις αξιολογούνται υπό κεντρικοποιημένες παραδοχές, ο…
  crossref Αλέξανδρος Καλαφατέλης 2026-07-13T09:33:14Z 置信度 0.70
• Federated Learning for Protecting Medical Data Privacy
  crossref Abhishek Reddy Punreddy 2023-06-15T15:53:00Z 置信度 0.70
• Graph representation learning in multimodal and federated scenarios
  crossref Xiaoxiong Zhang 2026-07-13T04:27:24Z 置信度 0.70
• Security and Privacy in Federated Learning–Based Internet of Medical Things
  crossref J. Swathi, G.R. Karpagam, Raghvendra Singh 2023-05-03T20:41:25Z 置信度 0.70
• Threats to Federated Learning
  crossref Lingjuan Lyu, Han Yu, Jun Zhao, Qiang Yang 2020-11-25T15:03:24Z 置信度 0.70
• Collaborative Federated Learning for Robots in Heterogeneous Environments
  This research investigates the performance of Federated Averaging (FedAvg) in simulated Federated Learning (FL) scenarios with varying degrees of environmental heterogeneity among robotic agents. The study explores the impact of data heterogeneity on both the …
  crossref Karlan Schneider 2026-08-10T22:24:52Z 置信度 0.70
• Kaizen-Grafting and OAuth2 RAR: A Sustainable Federated Learning Framework for Privacy-Preserving Business Analytics in Resource-Constrained Japanese SME Networks
  As we enter 2026, the industrialization of artificial intelligence (AI) has transitioned from an experimental noveltyto the backbone of enterprise operations. However, a significant “Digital Paradox” persists within the Japanese economy:while large corporation…
  datacite Kunal Rajneesh Sahal, Divyanshu Nagar, Pragya Vaishnav 2026 置信度 0.66
• Kaizen-Grafting and OAuth2 RAR: A Sustainable Federated Learning Framework for Privacy-Preserving Business Analytics in Resource-Constrained Japanese SME Networks
  As we enter 2026, the industrialization of artificial intelligence (AI) has transitioned from an experimental noveltyto the backbone of enterprise operations. However, a significant “Digital Paradox” persists within the Japanese economy:while large corporation…
  datacite Kunal Rajneesh Sahal, Divyanshu Nagar, Pragya Vaishnav 2026 置信度 0.66
• C^2Prompt: Class-aware Client Knowledge Interaction for Federated Continual Learning
  Federated continual learning (FCL) tackles scenarios of learning from continuously emerging task data across distributed clients, where the key challenge lies in addressing both temporal forgetting over time and spatial forgetting simultaneously. Recently, pro…
  datacite Xu, Kunlun, Feng, Yibo, Li, Jiangmeng, Qi, Yongsheng 等 2025 置信度 0.66 Machine Learning (cs.LG)Computer Vision and Pattern Recognition (cs.CV)FOS: Computer and information sciencesFOS: Computer and information sciences
• Federated Modality-specific Encoders and Partially Personalized Fusion Decoder for Multimodal Brain Tumor Segmentation
  Most existing federated learning (FL) methods for medical image analysis only considered intramodal heterogeneity, limiting their applicability to multimodal imaging applications. In practice, some FL participants may possess only a subset of the complete imag…
  datacite Liu, Hong, Wei, Dong, Dai, Qian, Wu, Xian 等 2026 置信度 0.66 Computer Vision and Pattern Recognition (cs.CV)FOS: Computer and information sciencesFOS: Computer and information sciences
• Towards a generic and resource-efficient testbed for federated learning in wireless sensor networks
  This paper presents a lightweight, modular and portable testbed for evaluating Federated Learning (FL) on embedded wireless sensor network (WSN) nodes. The testbed is designed for Tiny Edge and Little Edge level devices and supports structured data flow, multi…
  datacite Turchan, Krzysztof, Wołoszyn, Kamil, Piotrowski, Krzysztof 2025 置信度 0.66 Federated LearningWireless Sensor NetworksEmbedded SystemsDistributed ComputingFOS: Computer and information sciences
• UCM Framework: 44 Equations+
  ABSTRACTTHIS WHITE PAPER ESTABLISHES A COMPREHENSIVE MATHEMATICAL, LOGICAL, AND ENGINEERING-BASED PROOF STRUCTURE FOR THE RHEA-UCM AND ZADEIAN SENTINEL CYBERNETIC SYSTEMS. WE DOCUMENT AND VALIDATE THE 44 CORE EQUATIONS GOVERNING RECURSIVE PERCEPTION, ENTROPY M…
  datacite Roe, Paul 2025 置信度 0.66
• UCM Framework: 44 Equations+
  ABSTRACTTHIS WHITE PAPER ESTABLISHES A COMPREHENSIVE MATHEMATICAL, LOGICAL, AND ENGINEERING-BASED PROOF STRUCTURE FOR THE RHEA-UCM AND ZADEIAN SENTINEL CYBERNETIC SYSTEMS. WE DOCUMENT AND VALIDATE THE 44 CORE EQUATIONS GOVERNING RECURSIVE PERCEPTION, ENTROPY M…
  datacite Roe, Paul 2025 置信度 0.66
• A COMPREHENSIVE REVIEW OF QUANTUM MACHINE LEARNING FRAMEWORKS FOR PRIVACY-PRESERVING DATA HANDLING IN 5G-ENABLED HEALTHCARE ENVIRONMENTS
  The emergence of 5G networks has revolutionized healthcare delivery by enabling communication with ultra-low latency, massive connectivity, and quick access to IoT devices' medical data. The digitalization of healthcare has, however, introduced privacy, data s…
  datacite IJESAT 2026 置信度 0.66 Quantum Machine Learning, 5G Healthcare, Privacy-Preserving Data Handling, Quantum Cryptography, Quantum Key Distribution, Federated Learning.
• A COMPREHENSIVE REVIEW OF QUANTUM MACHINE LEARNING FRAMEWORKS FOR PRIVACY-PRESERVING DATA HANDLING IN 5G-ENABLED HEALTHCARE ENVIRONMENTS
  The emergence of 5G networks has revolutionized healthcare delivery by enabling communication with ultra-low latency, massive connectivity, and quick access to IoT devices' medical data. The digitalization of healthcare has, however, introduced privacy, data s…
  datacite IJESAT 2026 置信度 0.66 Quantum Machine Learning, 5G Healthcare, Privacy-Preserving Data Handling, Quantum Cryptography, Quantum Key Distribution, Federated Learning.
• Simple Yet Effective: Extracting Private Data Across Clients in Federated Fine-Tuning of Large Language Models
  Federated large language models (FedLLMs) enable cross-silo collaborative training among institutions while preserving data locality, making them appealing for privacy-sensitive domains such as law, finance, and healthcare. However, the memorization behavior o…
  datacite Hu, Yingqi, Zhang, Zhuo, Zhang, Jingyuan, Wang, Jinghua 等 2025 置信度 0.66 Computation and Language (cs.CL)Artificial Intelligence (cs.AI)FOS: Computer and information sciencesFOS: Computer and information sciences
• A Comparative Review of Machine Learning Approaches for Manufacturing Applications in Industry 4.0
  Industry 4.0 has redefined modern manufacturing by integrating cyber–physical systems, Industrial Internet of Things (IIoT), cloud–edge computing, and data-driven intelligence. Among these enablers, machine learning (ML) has emerged as a foundational technolog…
  datacite Veeru Paswan, Shalu Gupta, Gurleen 2026 置信度 0.66 Machine Learning, Deep Learning, Industry 4.0, Predictive Maintenance, Quality Inspection, Smart Manufacturing
• A Comparative Review of Machine Learning Approaches for Manufacturing Applications in Industry 4.0
  Industry 4.0 has redefined modern manufacturing by integrating cyber–physical systems, Industrial Internet of Things (IIoT), cloud–edge computing, and data-driven intelligence. Among these enablers, machine learning (ML) has emerged as a foundational technolog…
  datacite Veeru Paswan, Shalu Gupta, Gurleen 2026 置信度 0.66 Machine Learning, Deep Learning, Industry 4.0, Predictive Maintenance, Quality Inspection, Smart Manufacturing
• FedGIN: Federated Learning with Dynamic Global Intensity Non-linear Augmentation for Organ Segmentation using Multi-modal Images
  Medical image segmentation plays a crucial role in AI-assisted diagnostics, surgical planning, and treatment monitoring. Accurate and robust segmentation models are essential for enabling reliable, data-driven clinical decision making across diverse imaging mo…
  datacite Nagaraju, Sachin Dudda, Moradi, Ashkan, Abrahamsen, Bendik Skarre, Elschot, Mattijs 2025 置信度 0.66 Computer Vision and Pattern Recognition (cs.CV)Artificial Intelligence (cs.AI)FOS: Computer and information sciencesFOS: Computer and information sciences
• Benchmarking Catastrophic Forgetting Mitigation Methods in Federated Time Series Forecasting
  Catastrophic forgetting (CF) poses a persistent challenge in continual learning (CL), especially within federated learning (FL) environments characterized by non-i.i.d. time series data. While existing research has largely focused on classification tasks in vi…
  datacite Hallak, Khaled, Kem, Oudom 2025 置信度 0.66 Machine Learning (cs.LG)Distributed, Parallel, and Cluster Computing (cs.DC)Machine Learning (stat.ML)FOS: Computer and information sciencesFOS: Computer and information sciences
• Autonomous Cyber Resilience via a Co-Evolutionary Arms Race within a Fortified Digital Twin Sandbox
  The convergence of Information Technology and Operational Technology has exposed Industrial Control Systems to adaptive, intelligent adversaries that render static defenses obsolete. This paper introduces the Adversarial Resilience Co-evolution (ARC) framework…
  datacite Malikussaid, Sutiyo 2025 置信度 0.66 Cryptography and Security (cs.CR)Machine Learning (cs.LG)Systems and Control (eess.SY)FOS: Computer and information sciencesFOS: Computer and information sciences
• Catastrophic Forgetting Resilient One-Shot Incremental Federated Learning
  Modern big-data systems generate massive, heterogeneous, and geographically dispersed streams that are large-scale and privacy-sensitive, making centralization challenging. While federated learning (FL) provides a privacy-enhancing training mechanism, it assum…
  datacite Zaland, Obaidullah, Khan, Zulfiqar Ahmad, Bhuyan, Monowar 2026 置信度 0.66 Machine Learning (cs.LG)Distributed, Parallel, and Cluster Computing (cs.DC)FOS: Computer and information sciencesFOS: Computer and information sciences
• Guarding the Middle: Protecting Intermediate Representations in Federated Split Learning
  Big data scenarios, where massive, heterogeneous datasets are distributed across clients, demand scalable, privacy-preserving learning methods. Federated learning (FL) enables decentralized training of machine learning (ML) models across clients without data c…
  datacite Zaland, Obaidullah, Mistry, Sajib, Bhuyan, Monowar 2026 置信度 0.66 Machine Learning (cs.LG)Distributed, Parallel, and Cluster Computing (cs.DC)FOS: Computer and information sciencesFOS: Computer and information sciences
• Watch Out for the Lifespan: Evaluating Backdoor Attacks Against Federated Model Adaptation
  Large models adaptation through Federated Learning (FL) addresses a wide range of use cases and is enabled by Parameter-Efficient Fine-Tuning techniques such as Low-Rank Adaptation (LoRA). However, this distributed learning paradigm faces several security thre…
  datacite Vuillod, Bastien, Moellic, Pierre-Alain, Dutertre, Jean-Max 2025 置信度 0.66 Machine Learning (cs.LG)Cryptography and Security (cs.CR)FOS: Computer and information sciencesFOS: Computer and information sciences
• Identification of Movement Patterns Associated with Neurological Disorders Using Machine Vision
  The identification and quantification of abnormal movement patterns are central to the diagnosis, monitoring, and treatment of neurological disorders such as Parkinson’s disease (PD), stroke, cerebral palsy (CP), and dystonia. Machine vision the combination of…
  datacite Almasi, Mohammad 2026 置信度 0.66 machine vision, human pose estimation, gait analysis, Parkinson's disease, stroke, markerless motion capture
• Identification of Movement Patterns Associated with Neurological Disorders Using Machine Vision
  The identification and quantification of abnormal movement patterns are central to the diagnosis, monitoring, and treatment of neurological disorders such as Parkinson’s disease (PD), stroke, cerebral palsy (CP), and dystonia. Machine vision the combination of…
  datacite Almasi, Mohammad 2026 置信度 0.66 machine vision, human pose estimation, gait analysis, Parkinson's disease, stroke, markerless motion capture
• SDKP Framework — Complete System Architecture
  SDKP Framework — Complete System Architecture Author: Donald Paul Smith (FatherTime) Affiliation: Independent Researcher Abstract This work presents the SDKP framework, a unified symbolic–physical model connecting size, density, and rotational velocity to temp…
  datacite Smith, Donald 2026 置信度 0.66 FatherTimeSDKPSD&NMars timeLunar timeNASA
• SDKP Framework — Complete System Architecture
  SDKP Framework — Complete System Architecture Author: Donald Paul Smith (FatherTime) Affiliation: Independent Researcher Abstract This work presents the SDKP framework, a unified symbolic–physical model connecting size, density, and rotational velocity to temp…
  datacite Smith, Donald 2026 置信度 0.66 FatherTimeSDKPSD&NMars timeLunar timeNASA
• Toward Dignity-Aware AI: Next-Generation Elderly Monitoring from Fall Detection to ADL
  This position paper envisions a next-generation elderly monitoring system that moves beyond fall detection toward the broader goal of Activities of Daily Living (ADL) recognition. Our ultimate aim is to design privacy-preserving, edge-deployed, and federated A…
  datacite Shao, Xun, Otani, Aoba, Hirasuka, Yuto, Cai, Runji 等 2025 置信度 0.66 Machine Learning (cs.LG)Computer Vision and Pattern Recognition (cs.CV)Computers and Society (cs.CY)FOS: Computer and information sciencesFOS: Computer and information sciences
• White paper #1: HPC-Cloud and Quantum Computing: State of the Art and Innovation Roadmap
  This white paper presents an overview of the current state of the art in high-performance computing (HPC) and its convergence with cloud technologies, with a strategic focus on innovation management and exploitation. It outlines recent advances in cloud-based …
  datacite krokidas, panagiotis, Rekatsinas, Christoforos, Terlixidis, Periklis, Giannopoulos, Georgios 等 2025 置信度 0.66 High Performance ComputingQuantum computershybrid computing
• White paper #1: HPC-Cloud and Quantum Computing: State of the Art and Innovation Roadmap
  This white paper presents an overview of the current state of the art in high-performance computing (HPC) and its convergence with cloud technologies, with a strategic focus on innovation management and exploitation. It outlines recent advances in cloud-based …
  datacite krokidas, panagiotis, Rekatsinas, Christoforos, Terlixidis, Periklis, Giannopoulos, Georgios 等 2025 置信度 0.66 High Performance ComputingQuantum computershybrid computing
• Trusted Compute Units: A Framework for Chained Verifiable Computations
  Blockchain and distributed ledger technologies (DLTs) facilitate decentralized computations across trust boundaries. However, ensuring complex computations with low gas fees and confidentiality remains challenging. Recent advances in Confidential Computing -- …
  datacite Castillo, Fernando, Heiss, Jonathan, Werner, Sebastian, Tai, Stefan 2025 置信度 0.66 Cryptography and Security (cs.CR)FOS: Computer and information sciencesFOS: Computer and information sciences
• Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning
  Expensive communication cost is a common performance bottleneck in Federated Learning (FL), which makes it less appealing in real-world applications. Many communication-efficient FL methods focus on discarding a part of model updates mostly based on gradient m…
  datacite Kim, Jisoo, Kang, Sungmin, Lee, Sunwoo 2025 置信度 0.66 Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Impact of domain adaptation in deep learning for medical image classifications
  Domain adaptation (DA) is a quickly expanding area in machine learning that involves adjusting a model trained in one domain to perform well in another domain. While there have been notable progressions, the fundamental concept of numerous DA methodologies has…
  datacite Wu, Yihang, Chaddad, Ahmad 2026 置信度 0.66 Computer Vision and Pattern Recognition (cs.CV)FOS: Computer and information sciencesFOS: Computer and information sciences
• Vaccine Cold-Chain Cyber-Physical Logistics Dataset
  The released dataset, Vaccine Cold-Chain Cyber–Physical Logistics Dataset (VCC-CPLD), comprises 445,603 time-indexed records collected at a 1-minute sampling resolution, covering observations up to 31 December 2025, 23:59:00. Each record represents a cold-chai…
  datacite Davis, E Anne 2025 置信度 0.66
• Vaccine Cold-Chain Cyber-Physical Logistics Dataset
  The released dataset, Vaccine Cold-Chain Cyber–Physical Logistics Dataset (VCC-CPLD), comprises 445,603 time-indexed records collected at a 1-minute sampling resolution, covering observations up to 31 December 2025, 23:59:00. Each record represents a cold-chai…
  datacite Davis, E Anne 2025 置信度 0.66
• Blockchain Federated Learning for Sustainable Retail: Reducing Waste through Collaborative Demand Forecasting
  Effective demand forecasting is crucial for reducing food waste. However, data privacy concerns often hinder collaboration among retailers, limiting the potential for improved predictive accuracy. In this study, we explore the application of Federated Learning…
  datacite Turazza, Fabio, Neri, Alessandro, Pietri, Marcello, Butturi, Maria Angela 等 2026 置信度 0.66 Machine Learning (cs.LG)Artificial Intelligence (cs.AI)Cryptography and Security (cs.CR)FOS: Computer and information sciencesFOS: Computer and information sciences
• Artificial Intelligence in Clinically Validated Medical Imaging: Transforming Radiological Practice and Diagnostic Accuracy
  Artificial intelligence (AI) is transforming diagnostic radiology by enhancing image interpretation,pattern recognition, and clinical decision-making across multiple imaging modalities. This systematicliterature review critically evaluates the diagnostic perfo…
  datacite Shatha Abdullah Alkahtani, Shatha Abdullah Alkahtani, Raghad Hamad Alessa, Nouf Abdullah Alnumani 等 2026 置信度 0.66 artificial intelligencedeep learningdiagnostic imagingmachine learningradiology
• Artificial Intelligence in Clinically Validated Medical Imaging: Transforming Radiological Practice and Diagnostic Accuracy
  Artificial intelligence (AI) is transforming diagnostic radiology by enhancing image interpretation,pattern recognition, and clinical decision-making across multiple imaging modalities. This systematicliterature review critically evaluates the diagnostic perfo…
  datacite Shatha Abdullah Alkahtani, Shatha Abdullah Alkahtani, Raghad Hamad Alessa, Nouf Abdullah Alnumani 等 2026 置信度 0.66 artificial intelligencedeep learningdiagnostic imagingmachine learningradiology
• Federated Learning With Individualized Privacy Through Client Sampling
  With growing concerns about user data collection, individualized privacy has emerged as a promising solution to balance protection and utility by accounting for diverse user privacy preferences. Instead of enforcing a uniform level of anonymization for all use…
  datacite Lange, Lucas, Borchardt, Ole, Rahm, Erhard 2025 置信度 0.66 Machine Learning (cs.LG)Artificial Intelligence (cs.AI)Cryptography and Security (cs.CR)Computer Vision and Pattern Recognition (cs.CV)FOS: Computer and information sciences
• FedBGS: A Blockchain Approach to Segment Gossip Learning in Decentralized Systems
  Privacy-Preserving Federated Learning (PPFL) is a Decentralized machine learning paradigm that enables multiple participants to collaboratively train a global model without sharing their data with the integration of cryptographic and privacy-based techniques t…
  datacite Turazza, Fabio, Pietri, Marcello, Picone, Marco, Mamei, Marco 2026 置信度 0.66 Cryptography and Security (cs.CR)Artificial Intelligence (cs.AI)Distributed, Parallel, and Cluster Computing (cs.DC)Machine Learning (cs.LG)FOS: Computer and information sciences
• Federated Learning at the Forefront of Fairness: A Multifaceted Perspective
  Fairness in Federated Learning (FL) is emerging as a critical factor driven by heterogeneous clients' constraints and balanced model performance across various scenarios. In this survey, we delineate a comprehensive classification of the state-of-the-art fairn…
  datacite Mukhtiar, Noorain, Mahmood, Adnan, Zhou, Yipeng, Yang, Jian 等 2026 置信度 0.66 Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Föderierte Forschungsinfrastrukturen für ein lernendes Gesundheitssystem in der Akut-, Intensiv- und Notfallmedizin
  Bei der Behandlung kritisch kranker Patient:innen muss die medizinische Versorgung schnell und fehlerfrei erfolgen und sich an der verfügbaren Evidenz orientieren, die auf klinischen Daten fußt. Hierfür können sowohl kontrollierte klinische Studien als auch Re…
  datacite Bienzeisler, Jonas 2025 置信度 0.66 HochschulschriftEHR ; research infrastructure ; emergency medicine ; secondary use ; data federation ; real world data ; electronic health records
• Artificial Intelligence in Clinically Validated Medical Imaging: Transforming Radiological Practice and Diagnostic Accuracy
  Artificial intelligence (AI) is transforming diagnostic radiology by enhancing image interpretation,pattern recognition, and clinical decision-making across multiple imaging modalities. This systematicliterature review critically evaluates the diagnostic perfo…
  datacite Shatha Abdullah Alkahtani, Shatha Abdullah Alkahtani, Raghad Hamad Alessa, Nouf Abdullah Alnumani 等 2026 置信度 0.66 artificial intelligencedeep learningdiagnostic imagingmachine learningradiology
• Differential privacy for medical deep learning: methods, tradeoffs, and deployment implications
  Differential privacy (DP) is a key technique for protecting sensitive patient data in medical deep learning (DL). As clinical models grow more data-dependent, balancing privacy with utility and fairness has become a critical challenge. This scoping review synt…
  datacite Mohammadi, Marziyeh, Vejdanihemmat, Mohsen, Lotfinia, Mahshad, Rusu, Mirabela 等 2025 置信度 0.66 Machine Learning (cs.LG)Artificial Intelligence (cs.AI)FOS: Computer and information sciencesFOS: Computer and information sciences
• One-Shot Federated Learning with Classifier-Free Diffusion Models
  Federated learning (FL) enables collaborative learning without data centralization but introduces significant communication costs due to multiple communication rounds between clients and the server. One-shot federated learning (OSFL) addresses this by forming …
  datacite Zaland, Obaidullah, Jin, Shutong, Pokorny, Florian T., Bhuyan, Monowar 2025 置信度 0.66 Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• AI-driven Intrusion Detection for UAV in Smart Urban Ecosystems: A Comprehensive Survey
  UAVs have the potential to revolutionize urban management and provide valuable services to citizens. They can be deployed across diverse applications, including traffic monitoring, disaster response, environmental monitoring, and numerous other domains. Howeve…
  datacite Khanfor, Abdullah, Hamadi, Raby, Lasla, Noureddine, Ghazzai, Hakim 2026 置信度 0.66 Cryptography and Security (cs.CR)FOS: Computer and information sciencesFOS: Computer and information sciences
• Hetero-SplitEE: Split Learning of Neural Networks with Early Exits for Heterogeneous IoT Devices
  The continuous scaling of deep neural networks has fundamentally transformed machine learning, with larger models demonstrating improved performance across diverse tasks. This growth in model size has dramatically increased the computational resources required…
  datacite Oda, Yuki, Ono, Yuta, Nakamura, Hiroshi, Takase, Hideki 2025 置信度 0.66 Machine Learning (cs.LG)Artificial Intelligence (cs.AI)FOS: Computer and information sciencesFOS: Computer and information sciences
• FedMentor: Domain-Aware Differential Privacy for Heterogeneous Federated LLMs in Mental Health
  Privacy-preserving adaptation of Large Language Models (LLMs) in sensitive domains (e.g., mental health) requires balancing strict confidentiality with model utility and safety. We propose FedMentor, a federated fine-tuning framework that integrates Low-Rank A…
  datacite Sarwar, Nobin, Dipta, Shubhashis Roy 2025 置信度 0.66 Cryptography and Security (cs.CR)Artificial Intelligence (cs.AI)Computation and Language (cs.CL)Machine Learning (cs.LG)FOS: Computer and information sciences
• Differential Privacy-Driven Framework for Enhancing Heart Disease Prediction
  With the rapid digitalization of healthcare systems, there has been a substantial increase in the generation and sharing of private health data. Safeguarding patient information is essential for maintaining consumer trust and ensuring compliance with legal dat…
  datacite Otoum, Yazan, Nayak, Amiya 2025 置信度 0.66 Artificial Intelligence (cs.AI)Cryptography and Security (cs.CR)Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• FedCCA: Client-Centric Adaptation against Data Heterogeneity in Federated Learning on IoT Devices
  With the rapid development of the Internet of Things (IoT), AI model training on private data such as human sensing data is highly desired. Federated learning (FL) has emerged as a privacy-preserving distributed training framework for this purpuse. However, th…
  datacite Wang, Kaile, Cao, Jiannong, Yang, Yu, Li, Xiaoyin 等 2026 置信度 0.66 Machine Learning (cs.LG)Artificial Intelligence (cs.AI)FOS: Computer and information sciencesFOS: Computer and information sciences
• Y.I.N.-MEMORIA: A Comprehensive Privacy-Preserving Architecture for AI Conversation Management with Cryptographic Ordering Enforcement, Zero-Knowledge Governance, and Quantified Attack Defense
  We present Y.I.N.-MEMORIA, a comprehensive privacy-preserving architecture addressing fundamental vulnerabilities in AI conversation systems across all platforms, including large language model interfaces, enterprise AI assistants, domain-specific chatbots, an…
  datacite MAZARI, Ilyes Tarik 2026 置信度 0.66 Privacy-preserving AIDifferential privacyZero-knowledge proofsHomomorphic encryptionFederated learning
• Y.I.N.-MEMORIA: A Comprehensive Privacy-Preserving Architecture for AI Conversation Management with Cryptographic Ordering Enforcement, Zero-Knowledge Governance, and Quantified Attack Defense
  We present Y.I.N.-MEMORIA, a comprehensive privacy-preserving architecture addressing fundamental vulnerabilities in AI conversation systems across all platforms, including large language model interfaces, enterprise AI assistants, domain-specific chatbots, an…
  datacite MAZARI, Ilyes Tarik 2026 置信度 0.66 Privacy-preserving AIDifferential privacyZero-knowledge proofsHomomorphic encryptionFederated learning
• Efficient Transmission of Radiomaps via Physics-Enhanced Semantic Communications
  Enriching information of spectrum coverage, radiomap plays an important role in many wireless communication applications, such as resource allocation and network optimization. To enable real-time, distributed spectrum management, particularly in the scenarios …
  datacite Zhou, Yueling, Wijesinghe, Achintha, Wang, Yue, Zhang, Songyang 等 2025 置信度 0.66 Signal Processing (eess.SP)FOS: Electrical engineering, electronic engineering, information engineeringFOS: Electrical engineering, electronic engineering, information engineering
• QANBDG — Quantum-Adaptive Neural-Blockchain Defense Grid A Post-Quantum Autonomic Reference Architecture for Sovereign Defense and Classified Critical National Infrastructure Security
  QANBDG — Final Ultimate Edition (Clean Zenodo Description) Quantum-Adaptive Neural-Blockchain Defense Grid (QANBDG) A Post-Quantum, Autonomic Reference Architecture for Sovereign Defense and Classified Critical National Infrastructure (CNI) Security Abstract (…
  datacite Mazumdar, Bidyut 2026 置信度 0.66
• QANBDG — Quantum-Adaptive Neural-Blockchain Defense Grid A Post-Quantum Autonomic Reference Architecture for Sovereign Defense and Classified Critical National Infrastructure Security
  QANBDG — Final Ultimate Edition (Clean Zenodo Description) Quantum-Adaptive Neural-Blockchain Defense Grid (QANBDG) A Post-Quantum, Autonomic Reference Architecture for Sovereign Defense and Classified Critical National Infrastructure (CNI) Security Abstract (…
  datacite Mazumdar, Bidyut 2026 置信度 0.66
• FedCTTA: A Collaborative Approach to Continual Test-Time Adaptation in Federated Learning
  Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, making it ideal for privacy-sensitive applications. However, FL models often suffer performance degradation due to distribution shifts between tra…
  datacite Rajib, Rakibul Hasan, Iftee, Md Akil Raihan, Hossain, Mir Sazzat, Rahman, A. K. M. Mahbubur 等 2025 置信度 0.66 Machine Learning (cs.LG)Computer Vision and Pattern Recognition (cs.CV)FOS: Computer and information sciencesFOS: Computer and information sciences
• The Australian Imaging Service as the National Imaging Facility's Foundational Digital Research Infrastructure
  The first phase of the Australian Imaging Service (2020-24) saw the creation of the national federated software platform for secure data management, analysis, and informatics of biomedical imaging data through a series of projects funded by the ARDC Platforms …
  datacite Sullivan, Ryan 2025 置信度 0.66 InfrastructuresIdentifiers
• The Australian Imaging Service as the National Imaging Facility's Foundational Digital Research Infrastructure
  The first phase of the Australian Imaging Service (2020-24) saw the creation of the national federated software platform for secure data management, analysis, and informatics of biomedical imaging data through a series of projects funded by the ARDC Platforms …
  datacite Sullivan, Ryan 2025 置信度 0.66 InfrastructuresIdentifiers
• Generative AI in Power Platform CRM: Transforming Sales Pipelines with Copilot and Adaptive Sequences
  This article examines the transformative integration of generative artificial intelligence within Microsoft Power Platform CRM environments, focusing on the architectural framework and implementation methodologies of the 2025 Dynamics 365 Sales updates. It inv…
  datacite Nishanth Kumar Reddy Kesavareddi 2026 置信度 0.66
• Generative AI in Power Platform CRM: Transforming Sales Pipelines with Copilot and Adaptive Sequences
  This article examines the transformative integration of generative artificial intelligence within Microsoft Power Platform CRM environments, focusing on the architectural framework and implementation methodologies of the 2025 Dynamics 365 Sales updates. It inv…
  datacite Nishanth Kumar Reddy Kesavareddi 2026 置信度 0.66
• Enabling Weak Client Participation via On-device Knowledge Distillation in Heterogeneous Federated Learning
  Online Knowledge Distillation (KD) is recently highlighted to train large models in Federated Learning (FL) environments. Many existing studies adopt the logit ensemble method to perform KD on the server side. However, they often assume that unlabeled data col…
  datacite Lim, Jihyun, Jo, Junhyuk, Zhang, Tuo, Lee, Sunwoo 2025 置信度 0.66 Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Deliverable 2.15: Communication protocols
  Deliverable 2.15 on “Communication protocols” reports on the progress within Task 2.6 regarding communication protocols for data- and model-centric federated methods. In this deliverable, we report on how the Flower federated learning framework communicates du…
  datacite van der Wal, Douwe, Podareanu, Damian, Cardenas, Bryan, Biasin, Elisabetta 等 2025 置信度 0.66
• Deliverable 2.15: Communication protocols
  Deliverable 2.15 on “Communication protocols” reports on the progress within Task 2.6 regarding communication protocols for data- and model-centric federated methods. In this deliverable, we report on how the Flower federated learning framework communicates du…
  datacite van der Wal, Douwe, Podareanu, Damian, Cardenas, Bryan, Biasin, Elisabetta 等 2025 置信度 0.66
• Music Interaction Dataset
  This dataset captures real-world music listening behaviors and contextual metadata from January 2021 to January 2025, sampled at 30-minute intervals. It reflects the streaming activity of 50 anonymized users across a variety of devices and locations. Designed …
  datacite Sound Pulse Research Centre 2025 置信度 0.66
• Music Interaction Dataset
  This dataset captures real-world music listening behaviors and contextual metadata from January 2021 to January 2025, sampled at 30-minute intervals. It reflects the streaming activity of 50 anonymized users across a variety of devices and locations. Designed …
  datacite Sound Pulse Research Centre 2025 置信度 0.66
• Design of Intelligent Financial Risk Assessment Systems Using Machine Learning and SAP ERP Analytics
  In an era of unprecedented market volatility and high-frequency digital transactions, traditional retrospective financial risk management has become insufficient for modern enterprise governance. This review article investigates the design and implementation o…
  datacite Aadhya Mittal 2022 置信度 0.66 Financial Risk Assessment, Machine Learning, Sap S/4hana, Sap Business Technology Platform, Real-Time Analytics, Credit Risk Modeling, Fraud Detection.
• Design of Intelligent Financial Risk Assessment Systems Using Machine Learning and SAP ERP Analytics
  In an era of unprecedented market volatility and high-frequency digital transactions, traditional retrospective financial risk management has become insufficient for modern enterprise governance. This review article investigates the design and implementation o…
  datacite Aadhya Mittal 2022 置信度 0.66 Financial Risk Assessment, Machine Learning, Sap S/4hana, Sap Business Technology Platform, Real-Time Analytics, Credit Risk Modeling, Fraud Detection.
• LabSpace.coop Bylaws v3.0: Expeditionary Commons Governance Development Thread
  upload_type "dataset" publication_date "2025-12-29" title "LabSpace.coop Bylaws v3.0: Expeditionary Commons Governance Development Thread" creators 0 name "Walgemoed, Peter" affiliation "LabSpace.coop / Carelliance" orcid "0000-0000-0000-0000" description " Co…
  datacite Walgemoed, Peter 2025 置信度 0.66 1 "platform cooperatives" 2 "data stewardship" 3 "bioregional autonomy" 4 "federated commons" 5 "DNA-D3C framework" 6 "penta helix governance" 7 "sociocratic consent" 8 "wisdom artifacts" 9 "intergenerational stewardship" 10 "VooC AI" 11 "42-degree regenerative angle" 12 "fifth voice archive" 13 "mirab principle" 14 "summon bell protocol" 15 "ancient governance patterns" 16 "time-bound access" 17 "commons licensing" 18 "extraction prevention" 19 "collective learning"
• LabSpace.coop Bylaws v3.0: Expeditionary Commons Governance Development Thread
  upload_type "dataset" publication_date "2025-12-29" title "LabSpace.coop Bylaws v3.0: Expeditionary Commons Governance Development Thread" creators 0 name "Walgemoed, Peter" affiliation "LabSpace.coop / Carelliance" orcid "0000-0000-0000-0000" description " Co…
  datacite Walgemoed, Peter 2025 置信度 0.66 1 "platform cooperatives" 2 "data stewardship" 3 "bioregional autonomy" 4 "federated commons" 5 "DNA-D3C framework" 6 "penta helix governance" 7 "sociocratic consent" 8 "wisdom artifacts" 9 "intergenerational stewardship" 10 "VooC AI" 11 "42-degree regenerative angle" 12 "fifth voice archive" 13 "mirab principle" 14 "summon bell protocol" 15 "ancient governance patterns" 16 "time-bound access" 17 "commons licensing" 18 "extraction prevention" 19 "collective learning"
• Secure Data Integration Frameworks for Omni-channel Healthcare Marketing Systems
  The rapid digitalisation and increasing interconnection of healthcare marketing ecosystems require secure and interoperable data-integration frameworks. Omnichannel systems, a combination of clinical, behavioural and marketing data, are becoming increasingly i…
  datacite Chitiz Tayal 2025 置信度 0.66 Blockchain-based Healthcare Data ManagementPrivacy-Preserving Machine LearningOmnichannel Experience Platform (OEP)Customer Data Integration and AnalyticsFederated and Distributed Learning in Healthcare Marketing.
• Secure Data Integration Frameworks for Omni-channel Healthcare Marketing Systems
  The rapid digitalisation and increasing interconnection of healthcare marketing ecosystems require secure and interoperable data-integration frameworks. Omnichannel systems, a combination of clinical, behavioural and marketing data, are becoming increasingly i…
  datacite Chitiz Tayal 2025 置信度 0.66 Blockchain-based Healthcare Data ManagementPrivacy-Preserving Machine LearningOmnichannel Experience Platform (OEP)Customer Data Integration and AnalyticsFederated and Distributed Learning in Healthcare Marketing.
• Beyond Trade-offs: A Unified Framework for Privacy, Robustness, and Communication Efficiency in Federated Learning
  We propose Fed-DPRoC, a novel federated learning framework designed to jointly provide differential privacy (DP), Byzantine robustness, and communication efficiency. Central to our approach is the concept of robust-compatible compression, which allows reducing…
  datacite Xia, Yue, Jahani-Nezhad, Tayyebeh, Bitar, Rawad 2025 置信度 0.66 Machine Learning (cs.LG)Distributed, Parallel, and Cluster Computing (cs.DC)Information Theory (cs.IT)FOS: Computer and information sciencesFOS: Computer and information sciences
• A Hybrid Machine Learning And XAI Architecture For Intelligent Career Guidance Systems
  Industry 4.0 and artificial intelligence are shown to bring great change or disappear a large proportion of work, while new jobs are born With the dynamical background comes the demand for a smart career guidance system, which will provide advice that is perso…
  datacite Le Manh Ha, Nguyen Huu Quynh, Nguyen Tai Tuyen 2025 置信度 0.66
• A Hybrid Machine Learning And XAI Architecture For Intelligent Career Guidance Systems
  Industry 4.0 and artificial intelligence are shown to bring great change or disappear a large proportion of work, while new jobs are born With the dynamical background comes the demand for a smart career guidance system, which will provide advice that is perso…
  datacite Le Manh Ha, Nguyen Huu Quynh, Nguyen Tai Tuyen 2025 置信度 0.66
• A Hybrid Machine Learning And XAI Architecture For Intelligent Career Guidance Systems
  Industry 4.0 and artificial intelligence are shown to bring great change or disappear a large proportion of work, while new jobs are born With the dynamical background comes the demand for a smart career guidance system, which will provide advice that is perso…
  datacite Le Manh Ha, Nguyen Huu Quynh, Nguyen Tai Tuyen 2025 置信度 0.66
• A Hybrid Machine Learning And XAI Architecture For Intelligent Career Guidance Systems
  Industry 4.0 and artificial intelligence are shown to bring great change or disappear a large proportion of work, while new jobs are born With the dynamical background comes the demand for a smart career guidance system, which will provide advice that is perso…
  datacite Le Manh Ha, Nguyen Huu Quynh, Nguyen Tai Tuyen 2025 置信度 0.66
• A Hybrid Machine Learning And XAI Architecture For Intelligent Career Guidance Systems
  Industry 4.0 and artificial intelligence are shown to bring great change or disappear a large proportion of work, while new jobs are born With the dynamical background comes the demand for a smart career guidance system, which will provide advice that is perso…
  datacite Le Manh Ha, Nguyen Huu Quynh, Nguyen Tai Tuyen 2025 置信度 0.66
• Quantum Encryption for Secure Federated Learning Against Generative Adversarial Network Attacks
  Machine learning models in online environments are vulnerable to various adversarial attacks, such as those from generative adversarial networks (GANs) attacks and more powerful attacks based on recent advances in quantum computing. Federated Learning (FL), a …
  crossref Ervin Moore, Shabnam Rezapour, M. Hadi Amini 2025-01-28T11:34:33Z 置信度 0.70
• Towards Heterogeneity-Free: Client Selection for Federated Learning with Prototype Margin
  crossref Huaye Zhang, Yuan Liu 2026-03-19T20:04:01Z 置信度 0.70
• Gidd: Gradient Inversion Using Diffusion Model for Denoising in Federated Learning
  crossref Xuebo Wang, Hongguang Sun, Yi He 2025-03-11T13:39:20Z 置信度 0.70
• Notice of Removal: Twice the Gradient, Twice the Privacy Risk in Federated Learning? A Case Study of Federated Recommendation Systems
  crossref Zhenyu Deng, Ying Liu, Ming Tang, Xiangyu Zhao 2025-11-14T18:46:15Z 置信度 0.70
• Privacy Preservation in Federated Learning-Based Recommendation System
  crossref Shilpa Singhal, R. N. Ravikumar, Krupali Gosai, Santushti Betgeri 等 2025-08-08T17:48:19Z 置信度 0.70
• Replica tree-based federated learning using limited data
  crossref Ramona Ghilea, Islem Rekik 2025-02-22T16:25:38Z 置信度 0.70
• Federated Learning Strategies for Confidential Leukemia Detection from Medical Images
  crossref Jayonto Dutta Plabon, Mehjabin Hossain, Md. Arafat Kabir, Durjoy Mistry 等 2025-10-31T19:42:55Z 置信度 0.70
• IoT-Enhanced Additive Manufacturing and Federated Learning for Smart Healthcare Systems
  This chapter explores the privacy-utility trade-offs in IoT-enhanced additive manufacturing and federated learning systems within smart healthcare. IoT-driven additive manufacturing transforms healthcare by enabling customized medical devices and implants, whi…
  crossref Shaik Mahamad Shakeer, M. Rajasekhara Babu 2025-08-11T19:09:18Z 置信度 0.70
• Role of Federated Learning in Enhancing Security
  Federated Learning (FL), which prioritises data privacy and reduces centralised risks, has emerged as a revolutionary technique for enhancing security in distributed machine learning systems. As opposed to traditional methods that rely on aggregating raw data,…
  crossref Umme Ayeman Saqib Gani 2025-06-06T09:33:01Z 置信度 0.70