Manifest
发表于 2025-3-25 06:28:33
Adaptive Fault Diagnosis for Data Replication Systems,of the data replication environment, the fault diagnostic effort is both tedious and laborious. This paper proposes an approach to fault diagnosis of the data replication software through deep reinforcement learning. Empirical results show that the new method can identify and deduce the software faults quickly with high accuracy.
octogenarian
发表于 2025-3-25 10:37:44
The Stability Conditions of Salt Minerals,n hypergraph, sparse learning and adaptive graph are integrated into a framework. Finally, the suitable graph is obtained, which is inputted into GCN for semi-supervised learning. The experimental results of multi-type datasets show that our method is superior to other comparison algorithms in classification tasks.
deactivate
发表于 2025-3-25 15:22:50
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男生戴手铐
发表于 2025-3-25 19:20:42
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anaphylaxis
发表于 2025-3-25 23:48:06
Intention Recognition from Spatio-Temporal Representation of EEG Signals,ation and classification of signal features for specific thinking activities. Inspired by the structure and function of the human brain, we construct a neural computing model to explore the critical issues in the representation and real-time recognition of the state of specific thinking activities.
duplicate
发表于 2025-3-26 03:12:41
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aspersion
发表于 2025-3-26 05:38:32
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革新
发表于 2025-3-26 10:22:26
Contextual Bandit Learning for Activity-Aware Things-of-Interest Recommendation in an Assisted Livipresent a Reminder Care System to help Alzheimer patients live safely and independently in their homes. The proposed recommendation system is formulated based on a contextual bandit approach to tackle dynamicity in human activity patterns for accurate recommendations meeting user needs without their
SKIFF
发表于 2025-3-26 16:37:03
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微生物
发表于 2025-3-26 19:31:38
Experimental Analysis of Locality Sensitive Hashing Techniques for High-Dimensional Approximate Nea are known to suffer from the notorious . for high-dimensional data. Approximate searching techniques sacrifice some accuracy while returning . results for faster performance. Locality Sensitive Hashing (LSH) is a popular technique for finding approximate nearest neighbors. There are two main benefi