会议信息

iEDGE 2025: International Symposium on Edge intelligence, Trustworthy and Decentralized Artificial Intelligence

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截稿日期:
2025-08-01
通知日期:
2025-08-30
会议日期:
2025-10-14
会议地点:
Dubrovnik, Croatia
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会伴指数 (CP-I)

43.6 / 100
全站第 3,474 名 / 共 5,694 个会议 · 前 61%

人工智能与机器学习 第 430 / 741

证据有限：这个会议不在 CCF / ICORE / QUALIS 任何一份榜单里，也没有录用率数据，因此分数的大部分回落到了中性基准。
学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%) 无数据 —— 按中性基准 50 分计入 —
社区关注 (10%)
8
资料公开度 (15%)
35

用到的输入: 过去 24 个月打开过本页的研究者：2 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 25% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-07

征稿

iEDGE 2025 (International Symposium on Edge intelligence, Trustworthy and Decentralized Artificial Intelligence) is an academic conference held in Dubrovnik, Croatia on 2025-10-14. The paper submission deadline is 2025-08-01. Acceptance notifications are sent on 2025-08-30.

iEDGE 2025 is a premier international venue dedicated to advancing research and innovation at the intersection of trustworthy, decentralized, and distributed AI systems. As the scale, complexity, and societal impact of AI systems grow, ensuring trust, privacy, robustness, and decentralization becomes critical. We invite researchers, practitioners, and innovators from academia and industry to join us in exploring the new frontiers of Decentralized Artificial Intelligence, Trustworthy Machine Learning, and Secure Distributed Systems. Co-located with FLTA 2025, iEDGE focuses on scaling trustworthiness principles beyond federated learning into the broader decentralized AI ecosystem. The International Symposium on Edge intelligence, Trustworthy and Decentralized Artificial Intelligence (iEDGE 2025) addresses the use of advanced intelligent systems in providing trustworthy decentralized AI solutions in many fields, and the challenges, approaches, and future directions. We invite the submission of original papers on all topics related to trustworthy and decentralized artificial intelligence, with special interest in but not limited to: Topics of Interest Decentralized Artificial Intelligence Decentralized foundation model training and serving Peer-to-peer (P2P) inference networks Blockchain-based machine learning platforms Distributed optimization for large AI models Incentive mechanisms in decentralized AI systems Trustworthy AI Systems Bias mitigation, fairness, and accountability Verifiable decentralized model updates Explainability in distributed learning Robustness against adversarial attacks Security and Privacy Secure aggregation and differential privacy Trust mechanisms for model collaboration Resilient learning under malicious participants Secure Edge AI deployments Edge Intelligence Edge deployment of open foundation models Collaborative edge-cloud AI systems Privacy-preserving AI for constrained environments 5G/6G architectures for decentralized AI Resource allocation and scheduling
由 Dou Sun 最后更新于

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