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Stochastic Gradient Descent

SGD

Papers archive 2025-07-28

archive papers tagged: 2,021 · with a code link: 591 · where Syntology ran a sample: 192 (161 with a run with no instrument failure, 31 where every run was a failure of Syntology's instrument) Syntology

Show: all tagged papersonly where code ran (192 of 2,021 tagged: 161 with a run with no instrument failure, 31 where every run was a failure of Syntology's instrument)

Page 21 of 21: papers 2,001 to 2,021 of 2,021, newest first by the archive's date (ties by slug), in archive order.

Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code, as “N ran (of which C constructed an object rather than computing a result; K with no instrument failure: H honoured, V violated, P with no contract checked; I where Syntology's instrument failed) · U unverified”; the instrument figure counts failures of Syntology's instrument, not of the code. It is per sample and not a correctness claim. When the archive marks a repository official for the paper, the line starts with that repository's state (the archive's flag, not a verdict on who wrote the code; “community repositories only” when every sample that ran came from a community repository, “official: no sample here; runs from other or unrecorded repositories” when some came from a repository the paper names or has in its text, or from none recorded); hover it for the repositories the samples that ran came from.

• On the Computational Efficiency of Training Neural Networks
  5 Oct 2014 · 1 repository · arXiv:1410.1141
  Syntology 3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 3 harvested samples)
• Communication-Efficient Distributed Dual Coordinate Ascent
  4 Sep 2014 · 0 repositories · arXiv:1409.1458
• Randomized Block Coordinate Descent for Online and Stochastic Optimization
  1 Jul 2014 · 0 repositories · arXiv:1407.0107
• Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
  18 Jun 2014 · 14 repositories · arXiv:1406.4729
  Syntology 0 ran · 1 unverified (of 1 harvested sample)
• Accelerating Minibatch Stochastic Gradient Descent using Stratified Sampling
  13 May 2014 · 0 repositories · arXiv:1405.3080
• Some Improvements on Deep Convolutional Neural Network Based Image Classification
  19 Dec 2013 · 3 repositories · arXiv:1312.5402
• A Parallel SGD method with Strong Convergence
  4 Nov 2013 · 0 repositories · arXiv:1311.0636
• Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm
  21 Oct 2013 · 0 repositories · arXiv:1310.5715
• Online Tensor Methods for Learning Latent Variable Models
  3 Sep 2013 · 1 repository · arXiv:1309.0787
• Fast gradient descent for drifting least squares regression, with application to bandits
  11 Jul 2013 · 0 repositories · arXiv:1307.3176
• Concentration bounds for temporal difference learning with linear function approximation: The case of batch data and uniform sampling
  11 Jun 2013 · 0 repositories · arXiv:1306.2557
• Stochastic gradient descent algorithms for strongly convex functions at O(1/T) convergence rates
  9 May 2013 · 0 repositories · arXiv:1305.2218
• Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections
  19 Apr 2013 · 0 repositories · arXiv:1304.5504
• Efficient Distance Metric Learning by Adaptive Sampling and Mini-Batch Stochastic Gradient Descent (SGD)
  3 Apr 2013 · 0 repositories · arXiv:1304.1192
• Training Neural Networks with Stochastic Hessian-Free Optimization
  16 Jan 2013 · 0 repositories · arXiv:1301.3641
• Large Scale Distributed Deep Networks
  1 Dec 2012 · 0 repositories
• No More Pesky Learning Rates
  6 Jun 2012 · 0 repositories · arXiv:1206.1106
• Beating SGD: Learning SVMs in Sublinear Time
  1 Dec 2011 · 0 repositories
• Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
  1 Dec 2011 · 0 repositories
• HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
  28 Jun 2011 · 5 repositories · arXiv:1106.5730
  Syntology 16 ran (of which 0 constructed an object rather than computing a result; 16 with no instrument failure: 0 honoured, 0 violated, 16 with no contract checked; 0 where Syntology's instrument failed) · 8 unverified (of 24 harvested samples)
• Provable Guarantees on Learning Hierarchical Generative Models with Deep CNNs
  0 repositories