Keyword

large-scale machine learning

Description: Machine-learning methods and systems designed to train or perform inference with large datasets, models, or computational workloads.

Primary topic: Stochastic Gradient Optimization Techniques (35%)

OpenAlex ID: keywords/large-scale-machine-learning

XGBoost

2016 · Tianqi Chen, Carlos Guestrin · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 53,522

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Auto-Encoding Variational Bayes

2013 · Kingma, Diederik P, Welling, Max · UvA-DARE (University of Amsterdam) · 17,804

Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers

2010 · Stephen Boyd · now publishers, Inc. eBooks · 12,676

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

2016 · Abadi, Martín, Agarwal, Ashish, et al. · arXiv (Cornell University) · 9,405

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Federated Learning: Challenges, Methods, and Future Directions

2020 · Tian Li, Anit Kumar Sahu, et al. · IEEE Signal Processing Magazine · 6,179

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Large-Scale Machine Learning with Stochastic Gradient Descent

2010 · Léon Bottou · Physica-Verlag eBooks · 5,794

Optimization Methods for Large-Scale Machine Learning

2018 · Léon Bottou, Frank E. Curtis, et al. · SIAM Review · 3,151

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Adversarial Machine Learning at Scale

2016 · Kurakin, Alexey, Goodfellow, Ian, et al. · arXiv (Cornell University) · 2,326

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Making Large-Scale Support Vector Machine Learning Practical

1998 · Thorsten Joachims · The MIT Press eBooks · 1,625

Large scale metric learning from equivalence constraints

2012 · M. Kostinger, M. Hirzer, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 1,609

Pegasos: primal estimated sub-gradient solver for SVM

2010 · Shai Shalev-Shwartz, Yoram Singer, et al. · Mathematical Programming · 1,499

The Tradeoffs of Large-Scale Learning

2011 · Léon Bottou, Olivier Bousquet · The MIT Press eBooks · 1,200

Solving large scale linear prediction problems using stochastic gradient descent algorithms

2004 · Tong Zhang · 1,134

Ad click prediction

2013 · H. Brendan McMahan, Gary Holt, et al. · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 868

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Large-scale deep unsupervised learning using graphics processors

2009 · Rajat Raina, Anand Madhavan, et al. · International Conference on Machine Learning · 742

Reidentification by Relative Distance Comparison

2012 · Wei-Shi Zheng, Shaogang Gong, et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 720

Unleashing the Potential of Chatbots in Education: A State-Of-The-Art Analysis

2018 · Rainer Winkler, Matthias Soellner · Academy of Management Proceedings · 580

Automatic Database Management System Tuning Through Large-scale Machine Learning

2017 · Dana Van Aken, Andrew Pavlo, et al. · 573

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Large-Scale Kernel Machines

2007 · The MIT Press eBooks · 539

Sparsified SGD with Memory

2018 · Stich, Sebastian U., Cordonnier, Jean-Baptiste, et al. · arXiv (Cornell University) · 509

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Communication Efficient Distributed Machine Learning with the Parameter Server

2014 · Mu Li, David G. Andersen, et al. · neural information processing systems · 461

Large-Scale Machine Learning with Stochastic Gradient Descent

2011 · Léon Bottou · Chapman & Hall/CRC series in computer science & data analysis/Series in computer science and data analysis · 460

Communication Efficient Distributed Optimization using an Approximate Newton-type Method

2013 · Shamir, Ohad, Srebro, Nathan, et al. · arXiv (Cornell University) · 424

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Large-scale Multi-label Learning with Missing Labels

2013 · Yu, Hsiang-Fu, Jain, Prateek, et al. · arXiv (Cornell University) · 396

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Sample size selection in optimization methods for machine learning

2012 · Richard H. Byrd, Gillian M. Chin, et al. · Mathematical Programming · 369

Works count: 1,251

Citation count: 142,200