mlsanityData to 7 Oct 2026

Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization

arXiv 1309.2375 ↗First posted 10 Sep 2013stat.ML cs.LG cs.NAcited by 19

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Abstract (arXiv)

We introduce a proximal version of the stochastic dual coordinate ascent method and show how to accelerate the method using an inner-outer iteration procedure. We analyze the runtime of the framework and obtain rates that improve state-of-the-art results for various key machine learning optimization problems including SVM, logistic regression, ridge regression, Lasso, and multiclass SVM. Experiments validate our theoretical findings.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Sep 2013.

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Citing papers per year: 2021: 4; 2022: 8; 2023: 2; 2024: 3; 2025: 1; 2026: 1.

19 papers.

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  1. 2022Improving Self-Supervised Learning by Characterizing Idealized Representationscited by 33
  2. 2022Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensionscited by 23
  3. 2022Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methodscited by 14
  4. 2021Learning with Smooth Hinge Lossescited by 9
  5. 2022FedToken: Tokenized Incentives for Data Contribution in Federated Learningcited by 9
  6. 2022RECAPP: Crafting a More Efficient Catalyst for Convex Optimizationcited by 8
  7. 2021Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedbackcited by 6
  8. 2022On the Complexity of a Practical Primal-Dual Coordinate Methodcited by 6
  9. 2021First-Order Methods for Convex Optimizationcited by 4
  10. 2024Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioningcited by 4
  11. 2022A Stochastic Bundle Method for Interpolating Networkscited by 3
  12. 2021Structured Convolutional Kernel Networks for Airline Crew Schedulingcited by 2
7 more
  1. 2022Variance-Reduced Conservative Policy Iterationcited by 2
  2. 2024Multiple Locally Linear Kernel Machinescited by 1
  3. 2025FedAPM: Federated Learning via ADMM with Partial Model Personalizationcited by 1
  4. 2023Learning Large Scale Sparse Modelscited by 0
  5. 2023Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimizationcited by 0
  6. 2024Contractivity and linear convergence in bilinear saddle-point problems: An operator-theoretic approachcited by 0
  7. 2026Accelerating Single-Pass SGD for Generalized Linear Predictioncited by 0