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pro vyhledávání: '"Kim, Junghoon"'
Hypergraphs serve as a powerful tool for modeling complex relationships across domains like social networks, transactions, and recommendation systems. The (k,g)-core model effectively identifies cohesive subgraphs by assessing internal connections an
Externí odkaz:
http://arxiv.org/abs/2410.20350
Graph contrastive learning (GCL) generally requires a large number of samples. The one of the effective ways to reduce the number of samples is using hard negatives (e.g., Mixup). Designing mixing-based approach for GAD can be difficult due to imbala
Externí odkaz:
http://arxiv.org/abs/2410.20310
Codebook-based beam selection is one approach for configuring millimeter wave communication links. The overhead required to reconfigure the transmit and receive beam pair, though, increases in highly dynamic vehicular communication systems. Location
Externí odkaz:
http://arxiv.org/abs/2404.10936
Autor:
Kim, Junghoon, Kim, Taejoon, Das, Anindya Bijoy, Hosseinalipour, Seyyedali, Love, David J., Brinton, Christopher G.
Although user cooperation cannot improve the capacity of Gaussian two-way channels (GTWCs) with independent noises, it can improve communication reliability. In this work, we aim to enhance and balance the communication reliability in GTWCs by minimi
Externí odkaz:
http://arxiv.org/abs/2401.00477
Identifying cohesive subgraphs in hypergraphs is a fundamental problem that has received recent attention in data mining and engineering fields. Existing approaches mainly focus on a strongly induced subhypergraph or edge cardinality, overlooking the
Externí odkaz:
http://arxiv.org/abs/2309.04350
Unsupervised GAD methods assume the lack of anomaly labels, i.e., whether a node is anomalous or not. One common observation we made from previous unsupervised methods is that they not only assume the absence of such anomaly labels, but also the abse
Externí odkaz:
http://arxiv.org/abs/2308.11669
Graph anomaly detection has attracted considerable attention from various domain ranging from network security to finance in recent years. Due to the fact that labeling is very costly, existing methods are predominately developed in an unsupervised m
Externí odkaz:
http://arxiv.org/abs/2308.10918
In multi-user multi-antenna communications, it is well-known in theory that Rate-Splitting Multiple Access (RSMA) can achieve a higher spectral efficiency than both Space Division Multiple Access (SDMA) and Non-Orthogonal Multiple Access (NOMA). Howe
Externí odkaz:
http://arxiv.org/abs/2305.07361
The design of codes for feedback-enabled communications has been a long-standing open problem. Recent research on non-linear, deep learning-based coding schemes have demonstrated significant improvements in communication reliability over linear codes
Externí odkaz:
http://arxiv.org/abs/2304.13178