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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