暂无分享,去创建一个
Joseph Manzano | Abhinav Vishnu | Charles Siegel | Jeff Daily | A. Vishnu | C. Siegel | J. Daily | J. Manzano
[1] Alok Choudhary,et al. Synergistic Challenges in Data-Intensive Science and Exascale Computing: DOE ASCAC Data Subcommittee Report , 2013 .
[2] Prabhat,et al. Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets , 2016, ArXiv.
[3] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[4] Marc'Aurelio Ranzato,et al. Large Scale Distributed Deep Networks , 2012, NIPS.
[5] Geoffrey Zweig,et al. An introduction to computational networks and the computational network toolkit (invited talk) , 2014, INTERSPEECH.
[6] Gunnar Rätsch,et al. Support Vector Machines and Kernels for Computational Biology , 2008, PLoS Comput. Biol..
[7] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[8] Ian H. Witten,et al. The WEKA data mining software: an update , 2009, SKDD.
[9] Abhinav Vishnu,et al. Adaptive neuron apoptosis for accelerating deep learning on large scale systems , 2016, 2016 IEEE International Conference on Big Data (Big Data).
[10] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[11] Samy Bengio,et al. Revisiting Distributed Synchronous SGD , 2016, ArXiv.
[12] Alex Krizhevsky,et al. One weird trick for parallelizing convolutional neural networks , 2014, ArXiv.
[13] Jean-Daniel Fekete,et al. Analysis and Visualization , 2020, Neural Machine Translation.
[14] Kenta Oono,et al. Chainer : a Next-Generation Open Source Framework for Deep Learning , 2015 .
[15] Anthony Skjellum,et al. A High-Performance, Portable Implementation of the MPI Message Passing Interface Standard , 1996, Parallel Comput..
[16] Kesheng Wu,et al. Scientific Discovery at the Exascale , 2011 .
[17] Yoram Singer,et al. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization , 2011, J. Mach. Learn. Res..
[18] P. Baldi,et al. Searching for exotic particles in high-energy physics with deep learning , 2014, Nature Communications.
[19] Scott Shenker,et al. Spark: Cluster Computing with Working Sets , 2010, HotCloud.
[20] Geoffrey E. Hinton,et al. On the importance of initialization and momentum in deep learning , 2013, ICML.
[21] Abhinav Vishnu,et al. Distributed TensorFlow with MPI , 2016, ArXiv.
[22] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[23] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Anselm Vossen. Support Vector Machines in High Energy Physics , 2008 .
[26] Samy Bengio,et al. Torch: a modular machine learning software library , 2002 .
[27] Khushbu Agarwal,et al. Large Scale Frequent Pattern Mining Using MPI One-Sided Model , 2015, 2015 IEEE International Conference on Cluster Computing.
[28] Sanjay Ghemawat,et al. MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.
[29] Sergey Ioffe,et al. Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Jeyanthi Narasimhan,et al. Fast and Accurate Support Vector Machines on Large Scale Systems , 2015, 2015 IEEE International Conference on Cluster Computing.
[31] Abhinav Vishnu,et al. Fault Tolerant Frequent Pattern Mining , 2016, 2016 IEEE 23rd International Conference on High Performance Computing (HiPC).
[32] Razvan Pascanu,et al. Theano: new features and speed improvements , 2012, ArXiv.
[33] Tom White,et al. Hadoop: The Definitive Guide , 2009 .
[34] Abhinav Vishnu,et al. Fault Tolerant Support Vector Machines , 2016, 2016 45th International Conference on Parallel Processing (ICPP).
[35] Sorin Draghici,et al. Machine Learning and Its Applications to Biology , 2007, PLoS Comput. Biol..
[36] Chris H. Q. Ding,et al. Accelerating Deep Learning with Shrinkage and Recall , 2016, 2016 IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS).
[37] William Gropp,et al. MPI-2: Extending the Message-Passing Interface , 1996, Euro-Par, Vol. I.
[38] John Tran,et al. cuDNN: Efficient Primitives for Deep Learning , 2014, ArXiv.
[39] Abhinav Vishnu,et al. Fault Modeling of Extreme Scale Applications Using Machine Learning , 2016, 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS).
[40] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[41] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[42] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.