Zobrazeno 1 - 10
of 18 573
pro vyhledávání: '"Han, Dong"'
While traditional federated learning (FL) typically focuses on a star topology where clients are directly connected to a central server, real-world distributed systems often exhibit hierarchical architectures. Hierarchical FL (HFL) has emerged as a p
Externí odkaz:
http://arxiv.org/abs/2409.18448
Autor:
Han, Dong, Moon, Jihye, Díaz, Luís Roberto Mercado, Chen, Darren, Williams, Devan, Ding, Eric Y., Tran, Khanh-Van, McManus, David D., Chon, Ki H.
Most deep learning models of multiclass arrhythmia classification are tested on fingertip photoplethysmographic (PPG) data, which has higher signal-to-noise ratios compared to smartwatch-derived PPG, and the best reported sensitivity value for premat
Externí odkaz:
http://arxiv.org/abs/2409.06147
Over the past several years, various federated learning (FL) methodologies have been developed to improve model accuracy, a primary performance metric in machine learning. However, to utilize FL in practical decision-making scenarios, beyond consider
Externí odkaz:
http://arxiv.org/abs/2409.04901
Autor:
Lee, Ji-Eun, Wang, Aifeng, Chen, Shuzhang, Kwon, Minseong, Hwang, Jinwoong, Cho, Minhyun, Son, Ki-Hoon, Han, Dong-Soo, Choi, Jun Woo, Kim, Young Duck, Mo, Sung-Kwan, Petrovic, Cedomir, Hwang, Choongyu, Park, Se Young, Jang, Chaun, Ryu, Hyejin
Publikováno v:
Nature Communications 15, 3971 (2024)
The Berry curvature dipole (BCD) serves as a one of the fundamental contributors to emergence of the nonlinear Hall effect (NLHE). Despite intense interest due to its potential for new technologies reaching beyond the quantum efficiency limit, the in
Externí odkaz:
http://arxiv.org/abs/2408.11658
Autor:
Han, Dong-Jun, Fang, Wenzhi, Hosseinalipour, Seyyedali, Chiang, Mung, Brinton, Christopher G.
Devices located in remote regions often lack coverage from well-developed terrestrial communication infrastructure. This not only prevents them from experiencing high quality communication services but also hinders the delivery of machine learning se
Externí odkaz:
http://arxiv.org/abs/2408.09522
In this work, we leverage the pure skin color patch from the face image as the additional information to train an auxiliary skin color feature extractor and face recognition model in parallel to improve performance of state-of-the-art (SOTA) privacy-
Externí odkaz:
http://arxiv.org/abs/2407.05045
Autor:
Ma, Enhui, Zhou, Lijun, Tang, Tao, Zhang, Zhan, Han, Dong, Jiang, Junpeng, Zhan, Kun, Jia, Peng, Lang, Xianpeng, Sun, Haiyang, Lin, Di, Yu, Kaicheng
Using generative models to synthesize new data has become a de-facto standard in autonomous driving to address the data scarcity issue. Though existing approaches are able to boost perception models, we discover that these approaches fail to improve
Externí odkaz:
http://arxiv.org/abs/2406.01349
Autor:
Lim, Han-Dong, Lee, Donghwan
Multi-agent reinforcement learning (MARL) has witnessed a remarkable surge in interest, fueled by the empirical success achieved in applications of single-agent reinforcement learning (RL). In this study, we consider a distributed Q-learning scenario
Externí odkaz:
http://arxiv.org/abs/2405.14078
To improve the efficiency of reinforcement learning, we propose a novel asynchronous federated reinforcement learning framework termed AFedPG, which constructs a global model through collaboration among $N$ agents using policy gradient (PG) updates.
Externí odkaz:
http://arxiv.org/abs/2404.08003
Research interests in the robustness of deep neural networks against domain shifts have been rapidly increasing in recent years. Most existing works, however, focus on improving the accuracy of the model, not the calibration performance which is anot
Externí odkaz:
http://arxiv.org/abs/2402.15019