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Demystifying Parallel and Distributed Deep Learning
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inferredcites →https://doi.org/10.1002/9780470172261.ch1openalex-snapshot
Foundations of Genetic Algorithms
inferredcites →https://doi.org/10.1007/3-540-45014-9_1openalex-snapshot
Ensemble Methods in Machine Learning
inferredcites →https://doi.org/10.1007/978-3-030-01246-5_2openalex-snapshot
Progressive Neural Architecture Search
inferredcites →https://doi.org/10.1007/978-3-319-11179-7_36openalex-snapshot
Minimizing Computation in Convolutional Neural Networks
inferredcites →https://doi.org/10.1007/978-3-319-46493-0_32openalex-snapshot
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
inferredcites →https://doi.org/10.1007/978-3-540-24685-5_1openalex-snapshot
Optimization of Collective Reduction Operations
inferredcites →https://doi.org/10.1007/978-3-642-39593-2_1openalex-snapshot
Deep Learning of Representations: Looking Forward
inferredcites →https://doi.org/10.1007/978-3-642-40763-5_51openalex-snapshot
Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks
inferredcites →https://doi.org/10.1007/bf00992696openalex-snapshot
Simple statistical gradient-following algorithms for connectionist reinforcement learning
inferredcites →https://doi.org/10.1007/bf02165411openalex-snapshot
Gaussian elimination is not optimal
inferredcites →https://doi.org/10.1007/s11227-017-1994-xopenalex-snapshot
CHAOS: a parallelization scheme for training convolutional neural networks on Intel Xeon Phi
inferredcites →https://doi.org/10.1016/0016-0032(64)90390-4openalex-snapshot
Rounding errors in algebraic processes
inferredcites →https://doi.org/10.1016/0743-7315(86)90020-1openalex-snapshot
An asynchronous algorithm for scattering information between the active nodes of a multicomputer system
inferredcites →https://doi.org/10.1016/b978-0-08-050684-5.50008-2openalex-snapshot
A Comparative Analysis of Selection Schemes Used in Genetic Algorithms
inferredcites →https://doi.org/10.1016/b978-0-12-815480-9.00015-3openalex-snapshot
Evolving Deep Neural Networks
inferredcites →https://doi.org/10.1016/j.jpdc.2008.09.002openalex-snapshot
Bandwidth optimal all-reduce algorithms for clusters of workstations
inferredcites →https://doi.org/10.1016/s0893-6080(98)00116-6openalex-snapshot
On the momentum term in gradient descent learning algorithms
inferredcites →https://doi.org/10.1017/cbo9781107298019openalex-snapshot
Understanding Machine Learning
inferredcites →https://doi.org/10.1038/nature20101openalex-snapshot
Hybrid computing using a neural network with dynamic external memory
inferredcites →https://doi.org/10.1038/nature24270openalex-snapshot
Mastering the game of Go without human knowledge
inferredcites →https://doi.org/10.1093/comjnl/30.5.413openalex-snapshot
Implementing Neural Network Models on Parallel Computers
inferredcites →https://doi.org/10.1109/5.58337openalex-snapshot
Backpropagation through time: what it does and how to do it
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/72.279181openalex-snapshot
Learning long-term dependencies with gradient descent is difficult
inferredcites →https://doi.org/10.1109/78.205723openalex-snapshot
Efficient computation of the DFT with only a subset of input or output points
inferredcites →https://doi.org/10.1109/access.2014.2319813openalex-snapshot
Large-Scale Deep Belief Nets With MapReduce
inferredcites →https://doi.org/10.1109/asap.2017.7995254openalex-snapshot
Parallel Multi Channel convolution using General Matrix Multiplication
inferredcites →https://doi.org/10.1109/bigdata.2016.7840590openalex-snapshot
Predicting statistics of asynchronous SGD parameters for a large-scale distributed deep learning system on GPU supercomputers
inferredcites →https://doi.org/10.1109/cahpc.2018.8645935openalex-snapshot
Large Scale Language Modeling: Converging on 40GB of Text in Four Hours
inferredcites →https://doi.org/10.1109/cluster.2018.00058openalex-snapshot
Accelerating Deep Learning Frameworks with Micro-Batches
inferredcites →https://doi.org/10.1109/clustr.2000.888975openalex-snapshot
Proceedings IEEE International Conference on Cluster Computing. CLUSTER 2000
inferredcites →https://doi.org/10.1109/cvpr.1993.341010openalex-snapshot
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot
Going deeper with convolutions
inferredcites →https://doi.org/10.1109/cvpr.2016.284openalex-snapshot
FireCaffe: Near-Linear Acceleration of Deep Neural Network Training on Compute Clusters
inferredcites →https://doi.org/10.1109/cvpr.2016.435openalex-snapshot
Fast Algorithms for Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.243openalex-snapshot
Densely Connected Convolutional Networks
inferredcites →https://doi.org/10.1109/cvpr.2018.00907openalex-snapshot
Learning Transferable Architectures for Scalable Image Recognition
inferredcites →https://doi.org/10.1109/gamenets.2009.5137386openalex-snapshot
Asynchronous gossip algorithms for stochastic optimization
inferredcites →https://doi.org/10.1109/hpca.2017.52openalex-snapshot
Towards Pervasive and User Satisfactory CNN across GPU Microarchitectures
inferredcites →https://doi.org/10.1109/icapp.1997.651475openalex-snapshot
Proceedings of 3rd International Conference on Algorithms and Architectures for Parallel Processing
inferredcites →https://doi.org/10.1109/icapp.1997.651531openalex-snapshot
Parallel neural network training on Multi-Spert
inferredcites →https://doi.org/10.1109/icassp.2012.6288333openalex-snapshot
Scalable stacking and learning for building deep architectures
inferredcites →https://doi.org/10.1109/icassp.2013.6638950openalex-snapshot
Asynchronous stochastic gradient descent for DNN training
inferredcites →https://doi.org/10.1109/icassp.2014.6853593openalex-snapshot
On parallelizability of stochastic gradient descent for speech DNNS
inferredcites →https://doi.org/10.1109/icassp.2016.7472621openalex-snapshot
Listen, attend and spell: A neural network for large vocabulary conversational speech recognition
inferredcites →https://doi.org/10.1109/icassp.2016.7472805openalex-snapshot
Scalable training of deep learning machines by incremental block training with intra-block parallel optimization and blockwise model-update filtering
inferredcites →https://doi.org/10.1109/iccv.2015.123openalex-snapshot
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
inferredcites →https://doi.org/10.1109/icdm.2016.0028openalex-snapshot
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study
inferredcites →https://doi.org/10.1109/icdm.2017.161openalex-snapshot
GaDei: On Scale-Up Training as a Service for Deep Learning
inferredcites →https://doi.org/10.1109/icnn.1994.374845openalex-snapshot
Neural net simulation on parallel computers
inferredcites →https://doi.org/10.1109/icpads.2016.0126openalex-snapshot
Using Supercomputer to Speed up Neural Network Training
inferredcites →https://doi.org/10.1109/icpp.2014.36openalex-snapshot
Kylix: A Sparse Allreduce for Commodity Clusters
inferredcites →https://doi.org/10.1109/infcom.2005.1498447openalex-snapshot
Gossip algorithms: design, analysis and applications
inferredcites →https://doi.org/10.1109/ipdps.2009.5160935openalex-snapshot
Sparse collective operations for MPI
inferredcites →https://doi.org/10.1109/ipdps.2015.30openalex-snapshot
Notified Access: Extending Remote Memory Access Programming Models for Producer-Consumer Synchronization
inferredcites →https://doi.org/10.1109/ipdps.2017.36openalex-snapshot
Corrected Gossip Algorithms for Fast Reliable Broadcast on Unreliable Systems
inferredcites →https://doi.org/10.1109/ipdps.2019.00031openalex-snapshot
Improving Strong-Scaling of CNN Training by Exploiting Finer-Grained Parallelism
inferredcites →https://doi.org/10.1109/jproc.2017.2761740openalex-snapshot
Efficient Processing of Deep Neural Networks: A Tutorial and Survey
inferredcites →https://doi.org/10.1109/jrproc.1952.273898openalex-snapshot
A Method for the Construction of Minimum-Redundancy Codes
inferredcites →https://doi.org/10.1109/micro.1996openalex-snapshot
Proceedings of the 29th Annual IEEE/ACM International Symposium on Microarchitecture. MICRO 29
inferredcites →https://doi.org/10.1109/sc.2012.86openalex-snapshot
Optimization principles for collective neighborhood communications
inferredcites →https://doi.org/10.1109/sc.2016.53openalex-snapshot
Optimizing Memory Efficiency for Deep Convolutional Neural Networks on GPUs
inferredcites →https://doi.org/10.1109/tac.1986.1104412openalex-snapshot
Distributed asynchronous deterministic and stochastic gradient optimization algorithms
inferredcites →https://doi.org/10.1109/tbdata.2015.2472014openalex-snapshot
Petuum: A New Platform for Distributed Machine Learning on Big Data
inferredcites →https://doi.org/10.1109/tcad.2015.2474396openalex-snapshot
TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip
inferredcites →https://doi.org/10.1109/tpds.2016.2626289openalex-snapshot
Parallel Deep Neural Network Training for Big Data on Blue Gene/Q
inferredcites →https://doi.org/10.1109/wacv.2015.71openalex-snapshot
Image Classification Using Generative Neuro Evolution for Deep Learning
inferredcites →https://doi.org/10.1137/0330046openalex-snapshot
Acceleration of Stochastic Approximation by Averaging
inferredcites →https://doi.org/10.1137/070704277openalex-snapshot
Robust Stochastic Approximation Approach to Stochastic Programming
inferredcites →https://doi.org/10.1137/1.9781611970364openalex-snapshot
Arithmetic Complexity of Computations
inferredcites →https://doi.org/10.1137/1.9781611977523openalex-snapshot
Rounding Errors in Algebraic Processes
inferredcites →https://doi.org/10.1137/140954362openalex-snapshot
A Stochastic Quasi-Newton Method for Large-Scale Optimization
inferredcites →https://doi.org/10.1137/16m1080173openalex-snapshot
Optimization Methods for Large-Scale Machine Learning
inferredcites →https://doi.org/10.1145/1102351openalex-snapshot
Proceedings of the 22nd international conference on Machine learning - ICML '05
inferredcites →https://doi.org/10.1145/1273496openalex-snapshot
Proceedings of the 24th international conference on Machine learning
inferredcites →https://doi.org/10.1145/1362622.1362692openalex-snapshot
Implementation and performance analysis of non-blocking collective operations for MPI
inferredcites →https://doi.org/10.1145/1390156openalex-snapshot
Proceedings of the 25th international conference on Machine learning - ICML '08
inferredcites →https://doi.org/10.1145/155332.155333openalex-snapshot
LogP: towards a realistic model of parallel computation
inferredcites →https://doi.org/10.1145/1553374.1553486openalex-snapshot
Large-scale deep unsupervised learning using graphics processors
inferredcites →https://doi.org/10.1145/1995896.1995909openalex-snapshot
Generic topology mapping strategies for large-scale parallel architectures
inferredcites →https://doi.org/10.1145/2640087.2644155openalex-snapshot
Scaling Distributed Machine Learning with the Parameter Server
inferredcites →https://doi.org/10.1145/277651.277678openalex-snapshot
Thread scheduling for multiprogrammed multiprocessors
inferredcites →https://doi.org/10.1145/2783258.2783270openalex-snapshot
Performance Modeling and Scalability Optimization of Distributed Deep Learning Systems
inferredcites →https://doi.org/10.1145/2810103.2813687openalex-snapshot
Privacy-Preserving Deep Learning
inferredcites →https://doi.org/10.1145/2834892.2834893openalex-snapshot
Asynchronous parallel stochastic gradient descent
inferredcites →https://doi.org/10.1145/2908080.2908105openalex-snapshot
Latte: a language, compiler, and runtime for elegant and efficient deep neural networks
inferredcites →https://doi.org/10.1145/3020078.3021740openalex-snapshot
Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks?
inferredcites →https://doi.org/10.1145/3035918.3035933openalex-snapshot
Heterogeneity-aware Distributed Parameter Servers
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3067695.3084211openalex-snapshot
Hyper-parameter selection in deep neural networks using parallel particle swarm optimization
inferredcites →https://doi.org/10.1145/3079856.3080246openalex-snapshot
In-Datacenter Performance Analysis of a Tensor Processing Unit
inferredcites →https://doi.org/10.1145/3126908.3126912openalex-snapshot
Scaling deep learning on GPU and knights landing clusters
inferredcites →https://doi.org/10.1145/3140659.3080246openalex-snapshot
In-Datacenter Performance Analysis of a Tensor Processing Unit
inferredcites →https://doi.org/10.1145/3146347.3146355openalex-snapshot
Evolving Deep Networks Using HPC
inferredcites →https://doi.org/10.1145/3210377.3210394openalex-snapshot
Integrated Model, Batch, and Domain Parallelism in Training Neural Networks
inferredcites →https://doi.org/10.1145/321812.321815openalex-snapshot
The Parallel Evaluation of General Arithmetic Expressions
inferredcites →https://doi.org/10.1145/324133.324234openalex-snapshot
Scheduling multithreaded computations by work stealing
inferredcites →https://doi.org/10.1145/3295500openalex-snapshot
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
inferredcites →https://doi.org/10.1145/3295500.3356137openalex-snapshot
Large-batch training for LSTM and beyond
inferredcites →https://doi.org/10.1162/neco.1989.1.4.541openalex-snapshot
Backpropagation Applied to Handwritten Zip Code Recognition
inferredcites →https://doi.org/10.1162/neco.2006.18.7.1527openalex-snapshot
A Fast Learning Algorithm for Deep Belief Nets
inferredcites →https://doi.org/10.1184/r1/6475898openalex-snapshot
More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server
inferredcites →https://doi.org/10.1214/aoms/1177729586openalex-snapshot
A Stochastic Approximation Method
inferredcites →https://doi.org/10.1561/2200000016openalex-snapshot
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
inferredcites →https://doi.org/10.1561/9781601984616openalex-snapshot
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
inferredcites →https://doi.org/10.1609/aaai.v32i1.11728openalex-snapshot
AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training
inferredcites →https://doi.org/10.1609/aaai.v32i1.11876openalex-snapshot
DeepRebirth: Accelerating Deep Neural Network Execution on Mobile Devices
inferredcites →https://doi.org/10.1609/aaai.v33i01.33014780openalex-snapshot
Regularized Evolution for Image Classifier Architecture Search
inferredcites →https://doi.org/10.18653/v1/d17-1045openalex-snapshot
Sparse Communication for Distributed Gradient Descent
inferredcites →https://doi.org/10.18653/v1/w18-6301openalex-snapshot
Scaling Neural Machine Translation
inferredcites →https://doi.org/10.21437/interspeech.2014-211openalex-snapshot
Distributed learning of multilingual DNN feature extractors using GPUs
inferredcites →https://doi.org/10.21437/interspeech.2014-274openalex-snapshot
1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs
inferredcites →https://doi.org/10.21437/interspeech.2015-354openalex-snapshot
Scalable distributed DNN training using commodity GPU cloud computing
inferredcites →https://doi.org/10.3115/v1/d14-1179openalex-snapshot
Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
inferredcites →https://doi.org/10.3929/ethz-b-000093896openalex-snapshot
Energy, Memory, and Runtime Tradeoffs for Implementing Collective Communication Operations
inferredcites →https://doi.org/10.4230/oasics.dx.2026.15openalex-snapshot
AutoResearch Lite: a reproducible paper-inspired experiment runner (Adam mechanism reproduction and convergence-speed comparison)
inferredcites →https://doi.org/10.48550/arxiv.1012.1367openalex-snapshot
Optimal Distributed Online Prediction using Mini-Batches
inferredcites →https://doi.org/10.48550/arxiv.1106.5730openalex-snapshot
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
inferredcites →https://doi.org/10.48550/arxiv.1206.2944openalex-snapshot
Practical Bayesian Optimization of Machine Learning Algorithms
inferredcites →https://doi.org/10.48550/arxiv.1312.6184openalex-snapshot
Do Deep Nets Really Need to be Deep?
inferredcites →https://doi.org/10.48550/arxiv.1312.6186openalex-snapshot
GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training
inferredcites →https://doi.org/10.48550/arxiv.1404.5997openalex-snapshot
One weird trick for parallelizing convolutional neural networks
inferredcites →https://doi.org/10.48550/arxiv.1410.0759openalex-snapshot
cuDNN: Efficient Primitives for Deep Learning
inferredcites →https://doi.org/10.48550/arxiv.1502.02551openalex-snapshot
Deep Learning with Limited Numerical Precision
inferredcites →https://doi.org/10.48550/arxiv.1502.03044openalex-snapshot
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
inferredcites →https://doi.org/10.48550/arxiv.1503.02531openalex-snapshot
Distilling the Knowledge in a Neural Network
inferredcites →https://doi.org/10.48550/arxiv.1505.05972openalex-snapshot
Instant Learning: Parallel Deep Neural Networks and Convolutional Bootstrapping
inferredcites →https://doi.org/10.48550/arxiv.1506.06438openalex-snapshot
Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms
inferredcites →https://doi.org/10.48550/arxiv.1506.08272openalex-snapshot
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
inferredcites →https://doi.org/10.48550/arxiv.1508.02087openalex-snapshot
A Linearly-Convergent Stochastic L-BFGS Algorithm
inferredcites →https://doi.org/10.48550/arxiv.1511.00363openalex-snapshot
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
inferredcites →https://doi.org/10.48550/arxiv.1511.04561openalex-snapshot
8-Bit Approximations for Parallelism in Deep Learning
inferredcites →https://doi.org/10.48550/arxiv.1511.05950openalex-snapshot
Staleness-aware Async-SGD for Distributed Deep Learning
inferredcites →https://doi.org/10.48550/arxiv.1511.06314openalex-snapshot
Why M Heads are Better than One: Training a Diverse Ensemble of Deep Networks
inferredcites →https://doi.org/10.48550/arxiv.1512.00066openalex-snapshot
Sparse Tensor Algebra as a Parallel Programming Model
inferredcites →https://doi.org/10.48550/arxiv.1512.02595openalex-snapshot
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
inferredcites →https://doi.org/10.48550/arxiv.1512.06216openalex-snapshot
Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multiple Machines
inferredcites →https://doi.org/10.48550/arxiv.1602.02830openalex-snapshot
Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1
inferredcites →https://doi.org/10.48550/arxiv.1602.04283openalex-snapshot
Deep Learning on FPGAs: Past, Present, and Future
inferredcites →https://doi.org/10.48550/arxiv.1602.07360openalex-snapshot
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
inferredcites →https://doi.org/10.48550/arxiv.1602.07868openalex-snapshot
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1603.04467openalex-snapshot
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
inferredcites →https://doi.org/10.48550/arxiv.1603.07285openalex-snapshot
A guide to convolution arithmetic for deep learning
inferredcites →https://doi.org/10.48550/arxiv.1604.01946openalex-snapshot
Optimizing Performance of Recurrent Neural Networks on GPUs
inferredcites →https://doi.org/10.48550/arxiv.1604.06174openalex-snapshot
Training Deep Nets with Sublinear Memory Cost
inferredcites →https://doi.org/10.48550/arxiv.1604.07316openalex-snapshot
End to End Learning for Self-Driving Cars
inferredcites →https://doi.org/10.48550/arxiv.1606.00511openalex-snapshot
Distributed Hessian-Free Optimization for Deep Neural Network
inferredcites →https://doi.org/10.48550/arxiv.1606.03401openalex-snapshot
Memory-Efficient Backpropagation Through Time
inferredcites →https://doi.org/10.48550/arxiv.1606.04487openalex-snapshot
Omnivore: An Optimizer for Multi-device Deep Learning on CPUs and GPUs
inferredcites →https://doi.org/10.48550/arxiv.1606.06160openalex-snapshot
DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients
inferredcites →https://doi.org/10.48550/arxiv.1608.03983openalex-snapshot
SGDR: Stochastic Gradient Descent with Warm Restarts
inferredcites →https://doi.org/10.48550/arxiv.1609.07061openalex-snapshot
Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations
inferredcites →https://doi.org/10.48550/arxiv.1610.02132openalex-snapshot
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding
inferredcites →https://doi.org/10.48550/arxiv.1610.02357openalex-snapshot
Xception: Deep Learning with Depthwise Separable Convolutions
inferredcites →https://doi.org/10.48550/arxiv.1611.01578openalex-snapshot
Neural Architecture Search with Reinforcement Learning
inferredcites →https://doi.org/10.48550/arxiv.1611.04581openalex-snapshot
How to scale distributed deep learning?
inferredcites →https://doi.org/10.48550/arxiv.1612.04021openalex-snapshot
Generative Adversarial Parallelization
inferredcites →https://doi.org/10.48550/arxiv.1701.05130openalex-snapshot
On the Performance of Network Parallel Training in Artificial Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1704.04861openalex-snapshot
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
inferredcites →https://doi.org/10.48550/arxiv.1704.08792openalex-snapshot
DeepArchitect: Automatically Designing and Training Deep Architectures
inferredcites →https://doi.org/10.48550/arxiv.1705.07878openalex-snapshot
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning
inferredcites →https://doi.org/10.48550/arxiv.1705.08741openalex-snapshot
Train longer, generalize better: closing the generalization gap in large batch training of neural networks
inferredcites →https://doi.org/10.48550/arxiv.1705.09786openalex-snapshot
AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1706.02677openalex-snapshot
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
inferredcites →https://doi.org/10.48550/arxiv.1706.03292openalex-snapshot
Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters
inferredcites →https://doi.org/10.48550/arxiv.1706.03471openalex-snapshot
YellowFin and the Art of Momentum Tuning
inferredcites →https://doi.org/10.48550/arxiv.1706.05137openalex-snapshot
One Model To Learn Them All
inferredcites →https://doi.org/10.48550/arxiv.1708.03888openalex-snapshot
Large Batch Training of Convolutional Networks
inferredcites →https://doi.org/10.48550/arxiv.1708.05256openalex-snapshot
Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data
inferredcites →https://doi.org/10.48550/arxiv.1708.05344openalex-snapshot
SMASH: One-Shot Model Architecture Search through HyperNetworks
inferredcites →https://doi.org/10.48550/arxiv.1708.07308openalex-snapshot
Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads
inferredcites →https://doi.org/10.48550/arxiv.1710.09767openalex-snapshot
Meta Learning Shared Hierarchies
inferredcites →https://doi.org/10.48550/arxiv.1710.10196openalex-snapshot
Progressive Growing of GANs for Improved Quality, Stability, and Variation
inferredcites →https://doi.org/10.48550/arxiv.1711.00489openalex-snapshot
Don't Decay the Learning Rate, Increase the Batch Size
inferredcites →https://doi.org/10.48550/arxiv.1711.04528openalex-snapshot
Simple And Efficient Architecture Search for Convolutional Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1712.00559openalex-snapshot
Progressive Neural Architecture Search
inferredcites →https://doi.org/10.48550/arxiv.1712.01887openalex-snapshot
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
inferredcites →https://doi.org/10.48550/arxiv.1712.06567openalex-snapshot
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
inferredcites →https://doi.org/10.48550/arxiv.1802.03268openalex-snapshot
Efficient Neural Architecture Search via Parameter Sharing
inferredcites →https://doi.org/10.48550/arxiv.1802.04730openalex-snapshot
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions
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inferred← citeshttps://doi.org/10.1002/9781119700357.ch16openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/9781394305810.ch32openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/cpe.5547openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/cpe.5834openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/cpe.5923openalex-snapshot
Optimizing execution for pipelined‐based distributed deep learning in a heterogeneously networked GPU cluster
inferred← citeshttps://doi.org/10.1002/essoar.10506925.1openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/ett.4706openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/ima.70063openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/pssa.202000534openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/spe.2878openalex-snapshot
R2D2: A scalable deep learning toolkit for medical imaging segmentation
inferred← citeshttps://doi.org/10.1007/978-3-030-31756-0_3openalex-snapshot
Scaling Analysis of Specialized Tensor Processing Architectures for Deep Learning Models
inferred← citeshttps://doi.org/10.1007/978-3-030-36592-9_40openalex-snapshot
An Experimental Study of Deep Neural Networks on HPC Clusters
inferred← citeshttps://doi.org/10.1007/978-3-030-50417-5_29openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-030-50743-5_5openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-030-60265-9_15openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-030-63393-6_3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-030-64616-5_55openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-030-70604-3_2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-030-71058-3_10openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-030-85099-9_13openalex-snapshot
On Effects of Compression with Hyperdimensional Computing in Distributed Randomized Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-030-94876-4_4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-06156-1_30openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-08757-8_33openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-13832-4_21openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-24453-7_11openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-30442-2_19openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-30448-4_5openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-36024-4_43openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-39698-4_12openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-40843-4_44openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-49435-2_6openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-52426-4_15openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-54528-3_22openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-63783-4_29openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-66146-4_2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-72347-6_13openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-80268-3_4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-92517-7_7openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-93251-9_22openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-97554-7_11openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-00347-8_11openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-04160-9_3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-07109-5_18openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-07373-0_23openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-08369-2_1openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-11527-0_1openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-16577-0_56openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-22582-5_28openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-28672-7_6openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-31390-4_3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-15-9213-3_42openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-16-3764-3_5openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-19-8234-7_38openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-99-0769-4_6openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-99-8132-8_37openalex-snapshot
Distributed Training of Deep Neural Networks: Convergence and Case Study
inferred← citeshttps://doi.org/10.1007/s00607-021-00997-9openalex-snapshot
Using machine learning to model the training scalability of convolutional neural networks on clusters of GPUs
inferred← citeshttps://doi.org/10.1007/s00607-021-01029-2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10489-021-02588-9openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10586-021-03370-9openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10586-023-04234-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10586-024-04959-6openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10796-021-10190-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11222-026-10885-xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11227-021-03673-zopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11227-022-04417-3openalex-snapshot
HDNN: a cross-platform MLIR dialect for deep neural networks
inferred← citeshttps://doi.org/10.1007/s11227-022-04577-2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11227-022-04915-4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11227-024-06008-wopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11227-025-07451-zopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11227-025-08004-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11277-024-10952-4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11390-023-2894-6openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11390-024-3872-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11432-021-3532-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11633-023-1454-4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11704-022-0625-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11704-022-1749-6openalex-snapshot
swSpAMM: optimizing large-scale sparse approximate matrix multiplication on Sunway Taihulight
inferred← citeshttps://doi.org/10.1007/s12530-025-09723-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s12561-024-09449-2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s12583-024-0029-9openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s13042-023-01956-wopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s13042-025-02789-5openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s41468-023-00127-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s41781-021-00061-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s42484-023-00114-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s42514-026-00285-yopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s43674-026-00087-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s44207-024-00003-yopenalex-snapshot
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inferred← citeshttps://doi.org/10.1016/b978-0-32-385787-1.00022-1openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/b978-0-44-326484-9.00027-0openalex-snapshot
Multi-sensor Earth observation: outlook
inferred← citeshttps://doi.org/10.1016/b978-0-44-330259-6.00014-1openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/b978-0-443-45574-2.00025-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.aiopen.2021.08.002openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.cie.2025.111306openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.clineuro.2020.105718openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.cma.2025.118400openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.comcom.2022.12.007openalex-snapshot
CANTO: An actor model-based distributed fog framework supporting neural networks training in IoT applications
inferred← citeshttps://doi.org/10.1016/j.comnet.2025.111407openalex-snapshot
Libra: High-precision congestion control for datacenter networks with in-network allreduce
inferred← citeshttps://doi.org/10.1016/j.comnet.2025.111507openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.compfluid.2024.106498openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.compstruct.2025.119419openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.cose.2021.102402openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.cose.2024.103740openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.csbj.2020.08.003openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.drudis.2021.10.005openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.ecoinf.2024.102886openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.engappai.2023.107033openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.engappai.2024.108128openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.engappai.2025.112734openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.future.2021.03.006openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.future.2021.07.010openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.future.2022.02.024openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.future.2023.04.022openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.future.2023.10.010openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.future.2024.02.022openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.future.2024.07.016openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.future.2025.108052openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.future.2025.108260openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.future.2025.108317openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.icte.2021.08.014openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.iot.2023.101035openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.iswa.2023.200231openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jcp.2025.113910openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jksus.2020.101263openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jnca.2021.103111openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jpdc.2020.10.006openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jpdc.2020.11.005openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jpdc.2021.09.007openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jpdc.2022.05.009openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jpdc.2023.104767openalex-snapshot
SUARA: A scalable universal allreduce communication algorithm for acceleration of parallel deep learning applications
inferred← citeshttps://doi.org/10.1016/j.jpdc.2024.104879openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.knosys.2020.106002openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.knosys.2025.112965openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.laa.2022.12.017openalex-snapshot
On the convergence analysis of asynchronous SGD for solving consistent linear systems
inferred← citeshttps://doi.org/10.1016/j.matpr.2021.07.089openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.neucom.2021.08.143openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.neucom.2024.127258openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.neucom.2024.127345openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.neunet.2021.09.009openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.parco.2026.103208openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.peva.2025.102526openalex-snapshot
LLMEmu: A lightweight performance emulator for high-fidelity distributed LLM training
inferred← citeshttps://doi.org/10.1016/j.procs.2022.12.041openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.procs.2023.01.201openalex-snapshot
Study of Data and Model parallelism in Distributed Deep learning for Diabetic retinopathy classification
inferred← citeshttps://doi.org/10.1016/j.procs.2025.02.075openalex-snapshot
Effective Communication Compression Framework Using Federated Learning Privacy Model for Smart Grid
inferred← citeshttps://doi.org/10.1016/j.procs.2025.08.251openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.psep.2024.06.020openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.sysarc.2019.101635openalex-snapshot
A survey of techniques for optimizing deep learning on GPUs
inferred← citeshttps://doi.org/10.1016/j.sysarc.2026.103691openalex-snapshot
Covert feature-space adversarial perturbation using natural evolution strategies in distributed deep learning
inferred← citeshttps://doi.org/10.1016/j.sysarc.2026.103979openalex-snapshot
Robust detection of feature-space adversarial attacks in distributed edge inference using cascade Mahalanobis models
inferred← citeshttps://doi.org/10.1016/j.tcs.2025.115073openalex-snapshot
Asynchronous fully-decentralized SGD in the cluster-based model
inferred← citeshttps://doi.org/10.1038/s41467-026-71599-2openalex-snapshot
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inferred← citeshttps://doi.org/10.1038/s41586-020-03070-1openalex-snapshot
Parallel convolutional processing using an integrated photonic tensor core
inferred← citeshttps://doi.org/10.1038/s41598-019-47854-6openalex-snapshot
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inferred← citeshttps://doi.org/10.1038/s41598-020-69920-0openalex-snapshot
Variability and reproducibility in deep learning for medical image segmentation
inferred← citeshttps://doi.org/10.1049/aie2.70020openalex-snapshot
Dynamic Pipeline Scheduling for Hybrid Edge Collaboration in Multi‐Modal LLM Inference
inferred← citeshttps://doi.org/10.1049/cps2.12004openalex-snapshot
Developing normalization schemes for data isolated distributed deep learning
inferred← citeshttps://doi.org/10.1049/cps2.70031openalex-snapshot
Synchronisation, Optimisation and Adaptation of Machine Learning Techniques for Computer Vision in Cyber‐Physical Systems: A Comprehensive Analysis
inferred← citeshttps://doi.org/10.1080/0952813x.2024.2391778openalex-snapshot
Byzantine fault tolerance in distributed machine learning: a survey
inferred← citeshttps://doi.org/10.1080/1206212x.2025.2537892openalex-snapshot
Large-scale deep learning based face recognition utilizing vector database technologies: current trends, challenges, and solutions
inferred← citeshttps://doi.org/10.1080/17686733.2021.1918514openalex-snapshot
Deep convolutional neural networks for classifying breast cancer using infrared thermography
inferred← citeshttps://doi.org/10.1088/1742-6596/1999/1/012140openalex-snapshot
Classification of Imbalanced leukocytes Dataset using ANN-based Deep Learning
inferred← citeshttps://doi.org/10.1088/1742-6596/2580/1/012002openalex-snapshot
A layer-based random SGD for distributed training of RNNs
inferred← citeshttps://doi.org/10.1088/2632-2153/abd614openalex-snapshot
Deep learning in electron microscopy
inferred← citeshttps://doi.org/10.1088/2753-3751/ae2486openalex-snapshot
Empirically-calibrated H100 node power models for accurate AI training energy estimation
inferred← citeshttps://doi.org/10.1103/physrevresearch.6.l042040openalex-snapshot
Effective theory of collective deep learning
inferred← citeshttps://doi.org/10.1109/access.2020.3013541openalex-snapshot
Federated Learning: A Survey on Enabling Technologies, Protocols, and Applications
inferred← citeshttps://doi.org/10.1109/access.2020.3038112openalex-snapshot
SoftMemoryBox II: A Scalable, Shared Memory Buffer Framework for Accelerating Distributed Training of Large-Scale Deep Neural Networks
inferred← citeshttps://doi.org/10.1109/access.2020.3040083openalex-snapshot
HSIC Bottleneck Based Distributed Deep Learning Model for Load Forecasting in Smart Grid With a Comprehensive Survey
inferred← citeshttps://doi.org/10.1109/access.2021.3065406openalex-snapshot
Roulette: A Pruning Framework to Train a Sparse Neural Network From Scratch
inferred← citeshttps://doi.org/10.1109/access.2021.3070012openalex-snapshot
Accelerating Distributed SGD With Group Hybrid Parallelism
inferred← citeshttps://doi.org/10.1109/access.2022.3197646openalex-snapshot
AFSD: Adaptive Feature Space Distillation for Distributed Deep Learning
inferred← citeshttps://doi.org/10.1109/access.2023.3249153openalex-snapshot
Deep-Deterministic Policy Gradient Based Multi-Resource Allocation in Edge-Cloud System: A Distributed Approach
inferred← citeshttps://doi.org/10.1109/access.2023.3295412openalex-snapshot
The Current State and Challenges of Fairness in Federated Learning
inferred← citeshttps://doi.org/10.1109/access.2023.3296609openalex-snapshot
Accelerated Synchronous Model Parallelism Using Cooperative Process for Training Compute-Intensive Models
inferred← citeshttps://doi.org/10.1109/access.2023.3312572openalex-snapshot
Enabling Large Batch Size Training for DNN Models Beyond the Memory Limit While Maintaining Performance
inferred← citeshttps://doi.org/10.1109/access.2024.3475737openalex-snapshot
CroSSHeteroFL : Cross-Stratified Sampling Composition-Fitting to Federated Learning for Heterogeneous Clients
inferred← citeshttps://doi.org/10.1109/access.2024.3492314openalex-snapshot
Efficient Training of Large-Scale Neural Networks Using Linear Pipeline Broadcast
inferred← citeshttps://doi.org/10.1109/access.2025.3535085openalex-snapshot
A Survey on Parameter Server Architecture: Approaches for Optimizing Distributed Centralized Learning
inferred← citeshttps://doi.org/10.1109/access.2025.3602217openalex-snapshot
A Comprehensive Evaluation of Byzantine Attacks and Defenses Under Data Heterogeneity
inferred← citeshttps://doi.org/10.1109/access.2026.3664218openalex-snapshot
Convergence of HPC and Cloud Storage Systems for Deep Learning Workflows: An Evaluation of LustreFS and S3-Compatible Object Storage
inferred← citeshttps://doi.org/10.1109/acit58888.2023.10453894openalex-snapshot
Comparative Analysis of Sequential and Parallel Computing for Object Detection Using Deep Learning Model
inferred← citeshttps://doi.org/10.1109/acsos49614.2020.00041openalex-snapshot
Taming Resource Heterogeneity In Distributed ML Training With Dynamic Batching
inferred← citeshttps://doi.org/10.1109/ai4s56813.2022.00007openalex-snapshot
A Case Study on Coupling OpenFOAM with Different Machine Learning Frameworks
inferred← citeshttps://doi.org/10.1109/aiotc71250.2026.11688349openalex-snapshot
A Scalable Hybrid Deep Learning Model for Arabic Handwriting Recognition Using CNN, LSTM, Attention Mechanism, and Parallel Computing
inferred← citeshttps://doi.org/10.1109/bigdata.2018.8622065openalex-snapshot
Parallel Large-Scale Neural Network Training For Online Advertising
inferred← citeshttps://doi.org/10.1109/bigdata47090.2019.9006175openalex-snapshot
Auto-CNNp: a component-based framework for automating CNN parallelism
inferred← citeshttps://doi.org/10.1109/bigdata59044.2023.10386676openalex-snapshot
Distributed Quantum Learning with co-Management in a Multi-tenant Quantum System
inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10825421openalex-snapshot
An Overview of the Data-Loader Landscape: Comparative Performance Analysis
inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10825613openalex-snapshot
Federated Multi-task Learning in Distributed Networks
inferred← citeshttps://doi.org/10.1109/candarw.2018.00048openalex-snapshot
Hierarchical Distributed-Memory Multi-Leader MPI-Allreduce for Deep Learning Workloads
inferred← citeshttps://doi.org/10.1109/ccgrid.2019.00057openalex-snapshot
Exhaustive Study of Hierarchical AllReduce Patterns for Large Messages Between GPUs
inferred← citeshttps://doi.org/10.1109/ccgrid.2019.00064openalex-snapshot
Scalable Distributed DNN Training using TensorFlow and CUDA-Aware MPI: Characterization, Designs, and Performance Evaluation
inferred← citeshttps://doi.org/10.1109/ccgrid51090.2021.00021openalex-snapshot
Adaptive and Hierarchical Large Message All-to-all Communication Algorithms for Large-scale Dense GPU Systems
inferred← citeshttps://doi.org/10.1109/ccgrid51090.2021.00049openalex-snapshot
An Allreduce Algorithm and Network Co-design for Large-Scale Training of Distributed Deep Learning
inferred← citeshttps://doi.org/10.1109/ccgrid57682.2023.00033openalex-snapshot
Chronica: A Data-Imbalance-Aware Scheduler for Distributed Deep Learning
inferred← citeshttps://doi.org/10.1109/ccgrid57682.2023.00036openalex-snapshot
FreeTrain: A Framework to Utilize Unused Supercomputer Nodes for Training Neural Networks
inferred← citeshttps://doi.org/10.1109/ccgrid57682.2023.00040openalex-snapshot
Measuring the Impact of Gradient Accumulation on Cloud-based Distributed Training
inferred← citeshttps://doi.org/10.1109/ccgrid59990.2024.00031openalex-snapshot
Accelerating Large Language Model Training with Hybrid GPU-based Compression
inferred← citeshttps://doi.org/10.1109/ccgrid59990.2024.00036openalex-snapshot
Efficient Data-Parallel Continual Learning with Asynchronous Distributed Rehearsal Buffers
inferred← citeshttps://doi.org/10.1109/ccgrid68966.2026.00012openalex-snapshot
Scalable, Topology- and Multi-HCA-Aware Hierarchical GPU Allgather Using Parallel Rings
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