Large-scale neural networks
A Parallel Computing Platform for Training Large Scale Neural Networks
... Abstract—Artificial neural networks (ANNs) have been proved to be successfully used in a variety of pattern recogni- tion and data mining ...on large scale datasets are both data-intensive and ...
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Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines
... Weak scaling for Bert-48 on a cluster with 32 V100 GPUs, sequence length is 512. • Similar conclusion holds for BERT on the cluster with newer GPUs and heterogeneous interconnected[r] ...
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Applying Multiple Neural Networks on Large Scale Data
... of large data by applying multiple neural networks to learn several sub ...a large data set is difficult to learn at one ...the large data sets to be multiple subsets each of which is ...
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Large-Scale simulations of plastic neural networks on neuromorphic hardware
... this large-scale learning model can be efficiently simulated at scale using neuromorphic hardware and our simulations suggest that flexible systems such as SpiNNaker offer a promising tool for the ...
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LARGE-SCALE MALWARE CLASSIFICATION USING RANDOM PROJECTIONS AND NEURAL NETWORKS
... with neural networks with one or more hidden layers reducing the two-class error rate by more than 43% compared to logistic regression trained with all of the ...standard neural network topologies ...
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Large-Scale Simulation of Neural Networks with Biophysically Accurate Models on Graphics Processors
... simulation. Simulating large networks of HH neuron models on GPUs presents interesting chal- lenges and opportunities. Special care must be taken in algorithm development and code implementation in order to ...
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Modeling and Computational Framework for the Specification and Simulation of Large-scale Spiking Neural Networks
... currents (Logothetis, 2003). In multi-compartmental neuron models, the LFP can be determined at every point in space by computing the weighted sum of extracellular potentials over a large number of compartments ...
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PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition
... convolutional neural net- work ...audio neural networks (PANNs) trained on raw AudioSet recordings with a wide range of neural ...convolutional neural networks (CNNs) are used as ...
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Hierarchical Bipartite Graph Neural Networks: Towards Large-Scale E-commerce Applications
... Graph Neural Networks (GNNs), which do not learn hierarchical representations of graphs because they are inherently ...Graph Neural Network (HiGNN) to handle large-scale e-commerce ...
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Introducing a Clustering Technique into Recurrent Neural Networks for Solving Large-Scale Traveling Salesman Problems
... solve large-scale traveling salesman problems (TSPs) using re- current neural networks ...to large-scale TSPs. At first, a large-scale TSP is divided into some ...
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Robust Large Margin Deep Neural Networks
... results are also representative of the other datasets and network architectures. We can observe that using the Jacobian regularizer in (49) in- troduces additional computational time. This may not be critical if the ...
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Trainability and generalization of small-scale neural networks
... deep neural networks can generalize to unseen images better than ...with large number of data can obviously help closing the gap between training and test ...
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Simulation Infrastructure for Modeling Large Scale Neural Systems
... Neural systems are highly complex, structured, and can be viewed from many levels of abstraction. For example, the human brain is composed of roughly 100 billion neurons interconnected by 100 trillion synapses. ...
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Bayesian optimization of large scale biophysical networks
... Although the nature of these interactions remains to be characterised, this hypothesis is consistent with more functionally-oriented views, in which the brain is seen as a network of spatially segregated units, ...
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Dynamics in large scale networks
... and battle ranks they accrue the more friends they will tend to have; likely because they meet more avatars. Thus they have a lower clustering coefficient, since as degree grows clustering coefficient naturally decreases ...
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Malware Propagation in Large-Scale Networks
... In this paper, we study the distribution of malware in terms of networks (e.g., au- tonomous systems, ISP domains, abstract net- works of smartphones who share the same vulnerabilities) at large scales. In ...
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On querying large scale information networks
... information networks: how to find subgraph structures efficiently in a large information network? As a key ingredient of many network applications, this graph query has been frequently issued and extensive ...
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Building Large-Scale Bayesian Networks
... However, there have been serious problems for practitioners trying to use BNs to solve realistic problems. This is because, although the tools make it possible to execute large- scale BNs efficiently, there ...
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An NMS Architecture for Large-scale Networks
... Besides, networks which connect data centers and their users are getting larger and becoming more complex because of the growing bandwidth requirement and user ...such large-scale networks in ...
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Virtualization to build large scale networks
... Virtualization as a term broadly describes the separation of resources for services from the underlying physical delivery of those services. In other words, virtualization refers to the abstraction of fundamental ...
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