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Distributed algorithms are often beset by the straggler effect, where the slowest compute nodes in the system dictate the overall running time.
The eigenvalues of random symmetric matrices
Zoltán Füredi and János Komlós · 1981
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Complexity of finding dense subgraphs
Yuichi Asahiro, Refael Hassin, and Kazuo Iwama · 2002
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The largest eigenvalue of sparse random graphs
Michael Krivelevich and Benny Sudakov · 2003
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Improving mapreduce performance in heterogeneous environments
Matei Zaharia, Andy Konwinski, Anthony D Joseph, Randy H Katz, and Ion Stoica · 2008
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Large scale distributed deep networks
Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Mark Mao, Andrew Senior, Paul Tucker, Ke Yang, Quoc V Le, et al · 2012
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Expander graphs in pure and applied mathematics
Alexander Lubotzky · 2012
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Effective straggler mitigation: Attack of the clones
Ganesh Ananthanarayanan, Ali Ghodsi, Scott Shenker, and Ion Stoica · 2013
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Upper bounds for the largest eigenvalues of a bipartite graph
Jorma K Merikoski, Ravinder Kumar, and Ram Asrey Rajput · 2013
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Randomized extended kaczmarz for solving least squares
Anastasios Zouzias and Nikolaos M Freris · 2013
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Efficient task replication for fast response times in parallel computation
Da Wang, Gauri Joshi, and Gregory Wornell · 2014
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Replicated data placement for uncertain scheduling
Manmohan Chaubey and Erik Saule · 2015
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Reducing latency via redundant requests: Exact analysis
Kristen Gardner, Samuel Zbarsky, Sherwin Doroudi, Mor Harchol-Balter, and Esa Hyytia · 2015
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Consistency of spectral clustering in stochastic block models
Jing Lei, Alessandro Rinaldo, et al · 2015
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Coded mapreduce
Songze Li, Mohammad Ali Maddah-Ali, and A Salman Avestimehr · 2015
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Perturbed iterate analysis for asynchronous stochastic optimization
Horia Mania, Xinghao Pan, Dimitris Papailiopoulos, Benjamin Recht, Kannan Ramchandran, and Michael I Jordan · 2015
Speeding up distributed machine learning using codes
Kangwook Lee, Maximilian Lam, Ramtin Pedarsani, Dimitris Papailiopoulos, and Kannan Ramchandran · 2016
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When do redundant requests reduce latency?
Nihar B Shah, Kangwook Lee, and Kannan Ramchandran · 2016
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Rashish Tandon, Qi Lei, Alexandros G Dimakis, and Nikos Karampatziakis · 2016
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Concentration and regularization of random graphs
Can M Le, Elizaveta Levina, and Roman Vershynin · 2017
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Coded computation for multicore setups
Kangwook Lee, Ramtin Pedarsani, Dimitris Papailiopoulos, and Kannan Ramchandran · 2017
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Paleo: A performance model for deep neural networks
Hang Qi, Evan Sparks, and Ameet Talwalkar · 2017
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Adding gradient noise improves learning for very deep networks
Arvind Neelakantan, Luke Vilnis, Quoc V Le, Ilya Sutskever, Lukasz Kaiser, Karol Kurach, and James Martens · 2015
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Revisiting distributed synchronous sgd
Jianmin Chen, Rajat Monga, Samy Bengio, and Rafal Jozefowicz · 2016
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Short-dot: Computing large linear transforms distributedly using coded short dot products
Sanghamitra Dutta, Viveck Cadambe, and Pulkit Grover · 2016
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Gradient coding from cyclic mds codes and expander graphs
Netanel Raviv, Itzhak Tamo, Rashish Tandon, and Alexandros G Dimakis · 2017
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Coded computation over heterogeneous clusters
Amirhossein Reisizadehmobarakeh, Saurav Prakash, Ramtin Pedarsani, and Salman Avestimehr · 2017
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