External Memory Model
An "External Memory Model" is a computational model that characterizes algorithmic performance in terms of data transfer between a fast internal memory of limited size and a slow external memory of unbounded size, differing from other computational models by explicitly accounting for I/O costs as the dominant factor in time complexity.
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Hybrid computing using a neural network with dynamic external memory
Alex Graves, Greg Wayne, Malcolm Reynolds et al. · Nature · 2016 · 1.4K citations
Aspect Level Sentiment Classification with Deep Memory Network
Duyu Tang, Bing Qin, Ting Liu · 2016 · 1K citations · Full text
Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston et al. · arXiv (Cornell University) · 2015 · 692 citations · Full text
FFTs in external or hierarchical memory
David A. Bailey · The Journal of Supercomputing · 1990 · 289 citations
K-core decomposition of large networks on a single PC
Wissam Khaouid, Marina Barsky, Venkatesh Srinivasan et al. · Proceedings of the VLDB Endowment · 2015 · 214 citations
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Duke University
Durham, United States
10 h-index
20 publications
1.4K citations
Tsinghua University
Beijing, China
4 h-index
6 publications
111 citations
Humboldt-Universität zu Berlin
Berlin, Germany
4 h-index
8 publications
238 citations
University of California, Irvine
Irvine, United States
4 h-index
6 publications
170 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
4 h-index
10 publications
249 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
4 h-index
7 publications
561 citations
University of Cambridge
Cambridge, United Kingdom
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17 publications
699 citations

University of Waterloo
Waterloo, Canada
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6 publications
244 citations
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