Zobrazeno 1 - 10
of 513
pro vyhledávání: '"Tran, Nguyen H."'
Autor:
Nguyen, Tung-Anh, Le, Long Tan, Nguyen, Tuan Dung, Bao, Wei, Seneviratne, Suranga, Hong, Choong Seon, Tran, Nguyen H.
Publikováno v:
IEEE/ACM Transactions on Networking On page(s): 1-16 Print ISSN: 1063-6692 Online ISSN: 1558-2566 Digital Object Identifier: 10.1109/TNET.2024.3423780
With the proliferation of the Internet of Things (IoT) and the rising interconnectedness of devices, network security faces significant challenges, especially from anomalous activities. While traditional machine learning-based intrusion detection sys
Externí odkaz:
http://arxiv.org/abs/2407.07421
While astonishingly capable, large Language Models (LLM) can sometimes produce outputs that deviate from human expectations. Such deviations necessitate an alignment phase to prevent disseminating untruthful, toxic, or biased information. Traditional
Externí odkaz:
http://arxiv.org/abs/2405.15230
Beyond class frequency, we recognize the impact of class-wise relationships among various class-specific predictions and the imbalance in label masks on long-tailed segmentation learning. To address these challenges, we propose an innovative Pixel-wi
Externí odkaz:
http://arxiv.org/abs/2404.05393
Federated Learning (FL) is a prominent distributed learning paradigm facilitating collaboration among nodes within an edge network to co-train a global model without centralizing data. By shifting computation to the network edge, FL offers robust and
Externí odkaz:
http://arxiv.org/abs/2309.15659
In video streaming over HTTP, the bitrate adaptation selects the quality of video chunks depending on the current network condition. Some previous works have applied deep reinforcement learning (DRL) algorithms to determine the chunk's bitrate from t
Externí odkaz:
http://arxiv.org/abs/2306.15860
In the era of Internet of Things (IoT), network-wide anomaly detection is a crucial part of monitoring IoT networks due to the inherent security vulnerabilities of most IoT devices. Principal Components Analysis (PCA) has been proposed to separate ne
Externí odkaz:
http://arxiv.org/abs/2212.12121
In federated learning, participating clients typically possess non-i.i.d. data, posing a significant challenge to generalization to unseen distributions. To address this, we propose a Wasserstein distributionally robust optimization scheme called WAF
Externí odkaz:
http://arxiv.org/abs/2206.01432
Autor:
Hassan, Sheikh Salman, Kim, Do Hyeon, Tun, Yan Kyaw, Tran, Nguyen H., Saad, Walid, Hong, Choong Seon
Non-terrestrial networks (NTNs), which integrate space and aerial networks with terrestrial systems, are a key area in the emerging sixth-generation (6G) wireless networks. As part of 6G, NTNs must provide pervasive connectivity to a wide range of de
Externí odkaz:
http://arxiv.org/abs/2201.08605
Autor:
Van Treeck, Benjamin J., Olave, Maria C., Watkins, Ryan D., Lu, Haiyan, Moreira, Roger K., Mounajjed, Taofic, Johnson, Michael J., Smith, Carin Y., Ilyas, Sumera I., Tran, Nguyen H., Jenkins, Sarah M., Reed, Katelyn A., Smoot, Rory, Mahipal, Amit, Allende, Daniela, Graham, Rondell P.
Publikováno v:
In HPB July 2024 26(7):938-948
Autor:
Tran, Nguyen H, Nayak, Abhaya C
Recent years have seen growing interest in the development of self-driving vehicles that promise (or threaten) to replace human drivers with intelligent software. However, current self-driving cars still require human supervision and prompt takeover
Externí odkaz:
http://arxiv.org/abs/2107.14036