A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is
IEEE INFOCOM 2020 - IEEE Conference on Computer Communications
Costa-Perez (NEC Laboratories Europe, Germany) DeepAdapter: A Collaborative Deep Learning Framework for the Mobile Web Using Context-Aware Network Pruning Yakun Huang and Xiuquan Qiao (Beijing University ... A Zeroth-Order ADMM Algorithm for Stochastic Optimization over Distributed Processing Networks Zai Shi and Atilla Eryilmaz ( PDL: A Data Layout towards Fast Failure Recovery for Erasure-coded Distributed ...doi:10.1109/infocom41043.2020.9155443 fatcat:2oi6e5i2zjed5n25ft6ovaeudq
In this work, we propose an efficient internet behavior based recommendation framework with edge-cloud collaboration on deep CNNs (CoRec) to improve both the accuracy and speed for mobile recommendation ... Deep learning has achieved state-of-the-art accuracy and the traditional wisdom often hosts these computation-intensive models in powerful cloud centers. ... LcDNN  and DeepAdapter  provide lightweight collaborative frameworks for executing distributed DNN inference between the mobile web and edge server, which also rely on the edge server.  ...doi:10.1145/3526191 fatcat:v6auv3chabemxj2gc4v7uumlfe