Zobrazeno 1 - 10
of 624
pro vyhledávání: '"Jiang, Xiaowen"'
In developing efficient optimization algorithms, it is crucial to account for communication constraints -- a significant challenge in modern federated learning settings. The best-known communication complexity among non-accelerated algorithms is achi
Externí odkaz:
http://arxiv.org/abs/2407.07084
We present adaptive gradient methods (both basic and accelerated) for solving convex composite optimization problems in which the main part is approximately smooth (a.k.a. $(\delta, L)$-smooth) and can be accessed only via a (potentially biased) stoc
Externí odkaz:
http://arxiv.org/abs/2406.06398
Federated learning is a distributed optimization paradigm that allows training machine learning models across decentralized devices while keeping the data localized. The standard method, FedAvg, suffers from client drift which can hamper performance
Externí odkaz:
http://arxiv.org/abs/2404.08447
Autor:
Jiang, Xiaowen, Stich, Sebastian U.
The recently proposed stochastic Polyak stepsize (SPS) and stochastic line-search (SLS) for SGD have shown remarkable effectiveness when training over-parameterized models. However, in non-interpolation settings, both algorithms only guarantee conver
Externí odkaz:
http://arxiv.org/abs/2308.06058
Publikováno v:
IEEE Transactions on Image Processing (TIP), 2023
Halftoning aims to reproduce a continuous-tone image with pixels whose intensities are constrained to two discrete levels. This technique has been deployed on every printer, and the majority of them adopt fast methods (e.g., ordered dithering, error
Externí odkaz:
http://arxiv.org/abs/2304.12152
Deep neural networks have recently succeeded in digital halftoning using vanilla convolutional layers with high parallelism. However, existing deep methods fail to generate halftones with a satisfying blue-noise property and require complex training
Externí odkaz:
http://arxiv.org/abs/2207.11408
Autor:
Jiang, Xiaowen, Cambareri, Valerio, Agresti, Gianluca, Ugwu, Cynthia Ifeyinwa, Simonetto, Adriano, Cardinaux, Fabien, Zanuttigh, Pietro
Sparse active illumination enables precise time-of-flight depth sensing as it maximizes signal-to-noise ratio for low power budgets. However, depth completion is required to produce dense depth maps for 3D perception. We address this task with realis
Externí odkaz:
http://arxiv.org/abs/2205.12918
Autor:
XIA Caixia, JIANG Xiaowen, FANG Jingzhou, DUAN Dongmei, CAI Mingjing, YANG Zhixia, ZHANG Hongying
Publikováno v:
Zhongguo linchuang yanjiu, Vol 36, Iss 12, Pp 1816-1820 (2023)
Objective To explore the expression of sirtuin 6 (Sirt6) and lipid metabolism indicators in type 2 diabetic nephropathy (T2DN), and analyze their correlation with renal function indicators and their effectiveness in predicting T2DN. Methods The data
Externí odkaz:
https://doaj.org/article/28e47fdcdd4d4724a68cfe82e291f66b
Autor:
Jiang, Xiaowen, Sun, Lin, Lu, Yuyan, Wang, Hongyu, Shi, Jingwen, Yang, Liduo, Zhang, Lei, Lv, Rongguan, Jin, Zhong
Publikováno v:
In Journal of Power Sources 15 May 2024 602
Autor:
Zhou, Guanghu, Zhang, Jingjing, Liu, Shuang, Dong, Sainan, Cong, Yimei, Jiang, Xiaowen, Yu, Wenhui
Publikováno v:
In Journal of Thermal Biology May 2024 122