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检索条件"任意字段=5th IEEE/ACM Workshop on Machine Learning in HPC Environments, MLHPC 2019"
12 条 记 录,以下是1-10 订阅
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Proceedings of mlhpc 2019: 5th workshop on machine learning in hpc environments - Held in conjunction with SC 2019: the International Conference for High Performance Computing, Networking, Storage and Analysis
Proceedings of MLHPC 2019: 5th Workshop on Machine Learning ...
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5th ieee/acm workshop on machine learning in hpc environments, mlhpc 2019
the proceedings contain 8 papers. the topics discussed include: scalable hyperparameter optimization with lazy Gaussian processes;understanding scalability and fine-grain parallelism of synchronous data parallel train...
来源: 评论
Understanding Scalability and Fine-Grain Parallelism of Synchronous Data Parallel Training  5
Understanding Scalability and Fine-Grain Parallelism of Sync...
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5th ieee/acm workshop on machine learning in High Performance Computing environments (mlhpc)
作者: Li, Jiali Nicolae, Bogdan Wozniak, Justin Bosilca, George Univ Tennessee Knoxville TN 37996 USA Argonne Natl Lab Argonne IL 60439 USA
In the age of big data, deep learning has emerged as a powerful tool to extract insight and exploit its value, both in industry and scientific applications. With increasing complexity of learning models and amounts of... 详细信息
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Metaoptimization on a Distributed System for Deep Reinforcement learning  5
Metaoptimization on a Distributed System for Deep Reinforcem...
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5th ieee/acm workshop on machine learning in High Performance Computing environments (mlhpc)
作者: Heinrich, Greg Frosio, Iuri NVIDIA Nice France NVIDIA Santa Clara CA USA
Training intelligent agents through reinforcement learning (RL) is a notoriously unstable procedure. Massive parallelization on GPUs and distributed systems has been exploited to generate a large amount of training ex... 详细信息
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Scheduling optimization of parallel linear algebra algorithms using Supervised learning  5
Scheduling optimization of parallel linear algebra algorithm...
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5th ieee/acm workshop on machine learning in High Performance Computing environments (mlhpc)
作者: Laberge, Gabriel Shirzad, Shahrzad Diehl, Patrick Kaiser, Hartmut Prudhomme, Serge Lemoine, Adrian S. Polytech Montreal Dept Math & Ind Engn Montreal PQ Canada Louisiana State Univ Ctr Computat & Technol Baton Rouge LA 70803 USA
Linear algebra algorithms are used widely in a variety of domains, e.g machine learning, numerical physics and video games graphics. For all these applications, loop-level parallelism is required to achieve high perfo... 详细信息
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GradVis: Visualization and Second Order Analysis of Optimization Surfaces during the Training of Deep Neural Networks  5
GradVis: Visualization and Second Order Analysis of Optimiza...
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5th ieee/acm workshop on machine learning in High Performance Computing environments (mlhpc)
作者: Chatzimichailidis, Avraam Pfreundt, Franz-Josef Gauger, Nicolas R. Keuper, Janis Fraunhofer ITWM Competence Ctr High Performance Comp Kaiserslautern Germany Fraunhofer Ctr Machine Learning Berlin Germany TU Kaiserslautern Chair Sci Comp Kaiserslautern Germany Offenburg Univ Inst Machine Learning & Analyt Offenburg Germany
Current training methods for deep neural networks boil down to very high dimensional and non-convex optimization problems which are usually solved by a wide range of stochastic gradient descent methods. While these ap... 详细信息
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Scalable Hyperparameter Optimization with Lazy Gaussian Processes  5
Scalable Hyperparameter Optimization with Lazy Gaussian Proc...
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5th ieee/acm workshop on machine learning in High Performance Computing environments (mlhpc)
作者: Ram, Raju Mueller, Sabine Pfreundt, Franz-Josef Gauger, Nicolas R. Keuper, Janis Fraunhofer ITWM Competence Ctr High Performance Comp Kaiserslautern Germany Fraunhofer Ctr Machine Learning Berlin Germany TU Kaiserslautern Sci Comp Grp Kaiserslautern Germany Offenburg Univ Inst Machine Learning & Analyt Offenburg Germany
Most machine learning methods require careful selection of hyper-parameters in order to train a high performing model with good generalization abilities. Hence, several automatic selection algorithms have been introdu... 详细信息
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Parallel Data-Local Training for Optimizing Word2Vec Embeddings for Word and Graph Embeddings  5
Parallel Data-Local Training for Optimizing Word2Vec Embeddi...
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5th ieee/acm workshop on machine learning in High Performance Computing environments (mlhpc)
作者: Moon, Gordon E. Newman-Griffis, Denis Kim, Jinsung Sukumaran-Rajam, Aravind Fosler-Lussier, Eric Sadayappan, P. Ohio State Univ Comp Sci & Engn Columbus OH 43210 USA Univ Utah Sch Comp Salt Lake City UT USA
the Word2Vec model is a neural network-based unsupervised word embedding technique widely used in applications such as natural language processing, bioinformatics and graph mining. As Word2Vec repeatedly performs Stoc... 详细信息
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Message from the workshop chair
Proceedings of MLHPC 2019: 5th Workshop on Machine Learning ...
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Proceedings of mlhpc 2019: 5th workshop on machine learning in hpc environments - Held in conjunction with SC 2019: the International Conference for High Performance Computing, Networking, Storage and Analysis 2019年 V页
作者: Lim, Seung-Hwan Oak Ridge National Laboratory United States
来源: 评论
PAVE: An In Situ Framework for Scientific Visualization and machine learning Coupling  5
PAVE: An In Situ Framework for Scientific Visualization and ...
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5th ieee/acm International workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD)
作者: Leventhal, Samuel Kim, Mark Pugmire, David Univ Utah Sch Comp Sci Comp & Imaging Inst Salt Lake City UT 84112 USA Oak Ridge Natl Lab Oak Ridge TN USA
machine learning (ML) has emerged as a tool for understanding data at scale. However, this new methodology comes at a cost because even more hpc resources are required to generate ML algorithms. In addition to the com... 详细信息
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Using machine learning to reduce ensembles of geological models for oil and gas exploration  5
Using machine learning to reduce ensembles of geological mod...
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5th ieee/acm International workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD)
作者: Roubickova, Anna Brown, Nick Brown, Oliver thomson MacGregor, Lucy Stewart, Mike Univ Edinburgh EPCC Edinburgh Midlothian Scotland Cognit Geol Edinburgh Midlothian Scotland
Exploration using borehole drilling is a key activity in determining the most appropriate locations for the petroleum industry to develop oil fields. However, estimating the amount of Oil In Place (OIP) relies on comp... 详细信息
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