opportune
发表于 2025-3-28 15:40:37
Distributed Learning of Non-convex Linear Models with One Round of Communication data, and so has negligible computational cost. Compared with similar distributed estimators that merge locally trained models, OWA either has stronger statistical guarantees, is applicable to more models, or has a more computationally efficient merging procedure.
DEFT
发表于 2025-3-28 22:07:57
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预兆好
发表于 2025-3-29 01:22:43
Shift Happens: Adjusting Classifiers exact class distribution is known. We also demonstrate experimentally that, when in practice the class distribution is known only approximately, there is often still a reduction in loss depending on the amount of shift and the precision to which the class distribution is known.
Sarcoma
发表于 2025-3-29 06:08:52
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意外
发表于 2025-3-29 07:28:10
Conference proceedings 2020overy in Databases, ECML PKDD 2019, held in Würzburg, Germany, in September 2019..The total of 130 regular papers presented in these volumes was carefully reviewed and selected from 733 submissions; there are 10 papers in the demo track. ..The contributions were organized in topical sections named a
旧病复发
发表于 2025-3-29 14:11:10
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敲竹杠
发表于 2025-3-29 16:29:25
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LOPE
发表于 2025-3-29 21:01:18
SLSGD: Secure and Efficient Distributed On-device Machine Learningrithm with efficient communication and attack tolerance. The proposed algorithm has provable convergence and robustness under non-IID settings. Empirical results show that the proposed algorithm stabilizes the convergence and tolerates data poisoning on a small number of workers.
碎石
发表于 2025-3-30 02:11:36
978-3-030-46146-1Springer Nature Switzerland AG 2020
变形
发表于 2025-3-30 07:21:58
Machine Learning and Knowledge Discovery in Databases978-3-030-46147-8Series ISSN 0302-9743 Series E-ISSN 1611-3349