Distributed GraphLab: A Framework for Machine Learning in the Cloud

26 April 2012

Papers citing "Distributed GraphLab: A Framework for Machine Learning in the Cloud"

32 / 82 papers shown

Title
Machine Learning and Cloud Computing: Survey of Distributed and SaaS Solutions Daniel Pop 38 63 0 29 Mar 2016
Faster and Cheaper: Parallelizing Large-Scale Matrix Factorization on GPUs Wei Tan Liangliang Cao L. Fong 64 56 0 11 Mar 2016
Canary: A Scheduling Architecture for High Performance Cloud Computing Hang Qu Omid Mashayekhi David Terei P. Levis 64 23 0 03 Feb 2016
Strategies and Principles of Distributed Machine Learning on Big Data Eric Xing Qirong Ho P. Xie Wei-Ming Dai AI4CE 70 155 0 31 Dec 2015
BayesDB: A probabilistic programming system for querying the probable implications of data Vikash K. Mansinghka R. Tibbetts Jay Baxter Pat Shafto Baxter S. Eaves 62 38 0 15 Dec 2015
Speeding Up Distributed Machine Learning Using Codes Kangwook Lee Maximilian Lam Ramtin Pedarsani Dimitris Papailiopoulos Kannan Ramchandran 221 860 0 08 Dec 2015
A Framework for Computing on Large Dynamic Graphs Zhaoyu Dong 19 0 0 05 Dec 2015
Incremental Query Processing on Big Data Streams L. Fegaras 43 33 0 24 Nov 2015
Elastic Resource Allocation for Distributed Graph Processing Platforms Ravikant Dindokar Yogesh L. Simmhan 20 6 0 12 Oct 2015
Distributed Parameter Map-Reduce Qi Li 42 0 0 03 Oct 2015
Thinking Like a Vertex: a Survey of Vertex-Centric Frameworks for Distributed Graph Processing Ryan McCune Tim Weninger G. Madey 56 165 0 15 Jul 2015
Lightweight Asynchronous Snapshots for Distributed Dataflows Paris Carbone Gyula Fóra Stephan Ewen Seif Haridi K. Tzoumas 72 104 0 29 Jun 2015
Distributed Training of Structured SVM Ching-pei Lee Kai-Wei Chang Shyam Upadhyay Dan Roth 66 8 0 08 Jun 2015
Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning Mu Li D. Andersen Alex Smola FedML 27 15 0 18 May 2015
Effective Techniques for Message Reduction and Load Balancing in Distributed Graph Computation Da Yan James Cheng Yi Lu Wilfred Ng 68 118 0 02 Mar 2015
Model-Parallel Inference for Big Topic Models Xun Zheng Jin Kyu Kim Qirong Ho Eric Xing MoE AI4CE 87 7 0 10 Nov 2014
Factorbird - a Parameter Server Approach to Distributed Matrix Factorization Sebastian Schelter Venu Satuluri R. Zadeh 63 36 0 03 Nov 2014
FlashGraph: Processing Billion-Node Graphs on an Array of Commodity SSDs Da Zheng Disa Mhembere Randal C. Burns Joshua T. Vogelstein Carey E. Priebe A. Szalay 99 241 0 03 Aug 2014
Primitives for Dynamic Big Model Parallelism Seunghak Lee Jin Kyu Kim Xun Zheng Qirong Ho Garth A. Gibson Eric Xing 77 13 0 18 Jun 2014
Active Semi-Supervised Learning Using Sampling Theory for Graph Signals Akshay Gadde Aamir Anis Antonio Ortega 73 157 0 16 May 2014
Spinner: Scalable Graph Partitioning in the Cloud Claudio Martella Dionysios Logothetis Andreas Loukas Georgos Siganos 81 77 0 15 Apr 2014
DimmWitted: A Study of Main-Memory Statistical Analytics Ce Zhang Christopher Ré 173 146 0 28 Mar 2014
NetworKit: A Tool Suite for Large-scale Complex Network Analysis Christian Staudt A. Sazonovs Henning Meyerhenke 90 83 0 12 Mar 2014
Consistent Bounded-Asynchronous Parameter Servers for Distributed ML Jinliang Wei Wei-Ming Dai Abhimanu Kumar Xun Zheng Qirong Ho Eric Xing 44 13 0 30 Dec 2013
Petuum: A New Platform for Distributed Machine Learning on Big Data Eric P. Xing Qirong Ho Wei-Ming Dai Jin Kyu Kim Jinliang Wei Seunghak Lee Xun Zheng Junming Yin Abhimanu Kumar Eric Xing 109 35 0 30 Dec 2013
NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion Hyokun Yun Hsiang-Fu Yu Cho-Jui Hsieh S.V.N. Vishwanathan Inderjit Dhillon 111 124 0 01 Dec 2013
GoFFish: A Sub-Graph Centric Framework for Large-Scale Graph Analytics Yogesh L. Simmhan A. Kumbhare Charith Wickramaarachchi Soonil Nagarkar S. Ravi C. Raghavendra Viktor Prasanna GNN 79 111 0 23 Nov 2013
Blazes: Coordination Analysis for Distributed Programs P. Alvaro Neil Conway J. M. Hellerstein D. Maier 61 47 0 12 Sep 2013
Optimistic Concurrency Control for Distributed Unsupervised Learning Xinghao Pan Joseph E. Gonzalez Stefanie Jegelka Tamara Broderick Michael I. Jordan 74 35 0 30 Jul 2013
Rethinking Abstractions for Big Data: Why, Where, How, and What Mary W. Hall Robert M. Kirby Feifei Li Miriah D. Meyer Valerio Pascucci J. M. Phillips R. Ricci J. Merwe Suresh Venkatasubramanian AI4CE 35 9 0 14 Jun 2013
Accelerated Mini-Batch Stochastic Dual Coordinate Ascent Shai Shalev-Shwartz Tong Zhang ODL 131 151 0 12 May 2013
Mining Representative Unsubstituted Graph Patterns Using Prior Similarity Matrix Wajdi Dhifli Sabeur Aridhi E. M. Nguifo 62 25 0 08 Mar 2013