Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Chandra, Shashwat"'
In this paper, we present new algorithms for approximating All-Pairs Shortest Paths (APSP) in the Congested Clique model. We present randomized algorithms for weighted undirected graphs. Our first contribution is an $O(1)$-approximate APSP algorithm
Externí odkaz:
http://arxiv.org/abs/2405.02695
We revisit the classic broadcast problem, wherein we have $k$ messages, each composed of $O(\log{n})$ bits, distributed arbitrarily across a network. The objective is to broadcast these messages to all nodes in the network. In the distributed CONGEST
Externí odkaz:
http://arxiv.org/abs/2404.12930
Autor:
Zhang, David Junhao, Li, Kunchang, Wang, Yali, Chen, Yunpeng, Chandra, Shashwat, Qiao, Yu, Liu, Luoqi, Shou, Mike Zheng
Recently, MLP-Like networks have been revived for image recognition. However, whether it is possible to build a generic MLP-Like architecture on video domain has not been explored, due to complex spatial-temporal modeling with large computation burde
Externí odkaz:
http://arxiv.org/abs/2111.12527
Autor:
Singh, Ranjit, Ansari, Majibullah, Rao, Namrata, Chandra, Abhilash, Verma, Shashwat, Mishra, Prabhaker, Lohiya, Ayush
Publikováno v:
International Urology & Nephrology; Mar2024, Vol. 56 Issue 3, p1137-1145, 9p
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in