Proximal Gradient Descent

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Period ending 2026-09-21

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44 papers

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  1. Near-Optimal Pure Single-Loop Extragradient Method for Strongly Convex--Strongly Concave Minimax Optimization

    Sep 17, 2026Minhao Zhang, Zi XuConvex OptimizationProximal Gradient Descent

  2. Federated stochastic bilevel optimization with fully first-order gradients

    Sep 14, 2026Yihan Zhang, Rohit Dhaipule, Chiu C Tan +2Bilevel OptimizationProximal Gradient Descent

  3. Poisson-Corrector Complexity Bounds for Moreau--Yosida Unadjusted Langevin Sampling

    Sep 14, 2026Yuchen Xin, Zhihua ZhangLangevin DynamicsLipschitz Constant

  4. Projected Riemannian Gradient Descent for the Bures-Wasserstein Barycenter: Dimension-Independent Linear Convergence at Unit Step Size

    Sep 3, 2026A. AfhamProximal Gradient DescentLargest Eigenvalue

  5. A Globally Convergent Algorithm for Total Scaled-Gradient Variation via Cone-Constrained Bilinear Decomposition

    Aug 29, 2026Haibin Su, Chunlin Wu, Huibin Chang +1Image RestorationProximal Gradient Descent

  6. Active-Trace Complexity Bounds for Moreau--Yosida Unadjusted Langevin Sampling

    Aug 13, 2026Yuchen Xin, Zhihua ZhangLangevin DynamicsLipschitz Constant

  7. A Local-Linearly Convergent Algorithm for Nonconvex Equality-Constrained Optimization

    Aug 12, 2026Frank E. Curtis, Lingjun Guo, Daniel P. RobinsonProximal Gradient DescentNonconvex

  8. Adaptive Bregman Proximal Stochastic Gradient with a Stabilized Barzilai--Borwein Step Size

    Aug 12, 2026Chenhan Jin, Shengze Xu, Binghui Xie +4Proximal Gradient DescentVariance Reduction

  9. Exact Rank-Space KL Projection for Shared-Marginal Low-Rank Factors: Application to Doubly Stochastic Clustering

    Aug 9, 2026Enliang HuLow-Rank FactorizationProximal Gradient Descent

  10. Theoretical Foundations of Communication-Efficient, Robust, and Practical Distributed and Federated Optimization

    Aug 6, 2026Grigory MalinovskyFederated LearningDistributed Optimization

  11. A proximal subgradient method for nonconvex stochastic optimization under the Kurdyka-Łojasiewicz condition

    Aug 5, 2026Felipe Atenas, Alejandro Jofré, Pedro Pérez-Aros +1Stochastic Smooth Convex OptimizationProximal Gradient Descent

  12. Stochastic Saddle Avoidance Beyond Unit Excitation and Smoothness: A Pathwise Lyapunov-Perron Framework

    Aug 4, 2026Junwen Qiu, Bohao Ma, Andre Milzarek +1Proximal Gradient DescentStochastic Dynamics

  13. Generalized Quadratic Gradient: A New Direction in Optimization via the Fusion of Positive-Definite Curvature Matrices and Gradients into A Unified Framework

    Aug 3, 2026John ChiangCurvature-Aware Quadratic BanksProximal Gradient Descent

  14. Algorithmic Separation between Constant-Depth and Logarithmic-Depth Neural Networks

    Jul 28, 2026Yunwei Ren, Zihao Wang, Jason D. LeeDeep NetworkNeural Network

  15. Beyond Negative-Ridge Endpoints: Mixed-Sign Spectral Regularization via Negative-Shifted Gradient Descent

    Jul 24, 2026Peng ZhaoRegularization TechniquesQuadratic Slack Penalty

  16. Online Optimization of Difference-of-Convex Compositions with Smooth Mappings

    Jul 21, 2026Jingwei Ji, Jong-Shi Pang, Renyuan XuConvex OptimizationProximal Gradient Descent

  17. Domain Adaptation of Mismatched Proximal Denoiser for Plug-and-Play Image Reconstruction

    Jul 16, 2026Guixian Xu, Jinglai Li, Junqi TangImage ReconstructionImage Denoising

  18. Higher-Order Certified Robustness for Regression

    Jul 6, 2026Jie Zhang, Natalie FrankSmoothingNonparametric

  19. A Gradient Flow Perspective on Minimum MMD Estimation

    Jul 4, 2026Sophia Seulkee Kang, Louis Sharrock, Xiaoyuan Cheng +2Maximum Mean DiscrepancyProximal Gradient Descent

  20. Distributionally Robust Linear Regression With Block Lewis Weights

    Jun 30, 2026Naren Sarayu Manoj, Kumar Kshitij PatelLeast SquaresProximal Gradient Descent

  21. ITSPACE: Monotone Gaussian Optimal Transport Updates

    Jun 29, 2026Woojoo Na, Jennifer DyOptimal TransportCovariance Estimation

  22. Low-rank Updates in Slowly Time-varying Graphs for Spatial-Temporal Signal Interpolation

    Jun 22, 2026Saghar Bagheri, Gene Cheung, Tim Eadie +1Temporal Graph Neural NetworksSignal Processing

  23. Constrained Variable Projection for Structured Problems

    Jun 22, 2026Emanuele Zangrando, Sara Venturini, Francesco Rinaldi +1Proximal Gradient DescentBilevel Optimization

  24. Exact Schur-Sylvester Dimensionality Reductions for Non-Smooth Stochastic Complexity and Manifold Sampling

    Jun 22, 2026Trenton Lau, Gary P. T. ChoiMaximum LikelihoodOptimal Sample Complexity

  25. Spectral DPPs via NEPv: A Scalable Continuous Relaxation of Determinantal MAP for Diversity-Aware Data Selection

    Jun 17, 2026Richard Yi Da XuLargest EigenvalueKernel Method

  26. Bidirectional Random Projections

    Jun 9, 2026Chao Lan, Luyuan YangLeast SquaresLow-Rank Factorization

  27. Predictive Coding with Bayesian Priors via Proximal Gradients

    Jun 6, 2026Francesco BulloPredictive CodingBackpropagation

  28. The Sharp Phase Transition of Tyler's M-Estimator for Robust Subspace Recovery

    Jun 4, 2026Gilad Lerman, Teng ZhangSparse RecoveryEstimators

  29. A Nonmonotone Gradient-Based Algorithm for Symmetric Nonnegative Matrix Factorization and Graph Clustering

    Jun 1, 2026Ryan Swart, Johannes BrustNonnegative Matrix FactorizationProximal Gradient Descent

  30. Riemannian Optimization for Hadamard Products of Low-Rank Matrices

    May 31, 2026Pratik Jawanpuria, Ankish Chandresh, Bamdev MishraRiemannian OptimizationLow-Rank Factorization

  31. A Decentralized LiDAR-SLAM System with Certifiably Optimal Pose Graph Optimization

    May 24, 2026Baoshan Song, Feng Huang, Li-Ta HsuRobust Lidar-Inertial OdometryProximal Gradient Descent

  32. Proximal basin hopping: global optimization with guarantees

    May 18, 2026Guillaume Lauga, Cesare Molinari, Samuel VaiterProximal Gradient DescentFlat Minima

  33. Dynamic Elliptical Graph Factor Models via Riemannian Optimization with Geodesic Temporal Regularization

    May 18, 2026Chuansen Peng, Xiaojing ShenRiemannian ManifoldsFactor Graphs

  34. A proximal gradient algorithm for composite log-concave sampling

    May 12, 2026Linghai Liu, Sinho ChewiNon-Log-ConcaveProximal Gradient Descent

  35. Locally Near Optimal Piecewise Linear Regression in High Dimensions via Difference of Max-Affine Functions

    May 7, 2026Haitham Kanj, Kiryung LeeProximal Gradient DescentStochastic Gradient Descent

  36. Distributionally Robust Multi-Objective Optimization

    May 7, 2026Yufeng Yang, Fangning Zhuo, Ziyi Chen +2Multi-Objective OptimizationProximal Gradient Descent

  37. A Provably Convergent and Practical Algorithm for Gromov--Wasserstein Optimal Transport

    May 5, 2026Ling Liang, Lei YangGromov--WassersteinOptimal Transport

  38. Decentralized Proximal Stochastic Gradient Langevin Dynamics

    May 1, 2026Mohammad Rafiqul Islam, Lingjiong ZhuProximal Gradient DescentGibbs Measures

  39. Gradient Regularized Newton Boosting Trees with Global Convergence

    May 1, 2026Nikita Zozoulenko, Daniel Falkowski, Thomas Cass +1Gradient Boosted TreeProximal Gradient Descent

  40. FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection

    Apr 27, 2026Yutong He, Zhengyang Huang, Jiahe Geng +1Federated LearningFedavg

  41. Quasi-Quadratic Gradient: A New Direction for Accelerating the BFGS Method in Quasi-Newton Optimization

    Apr 27, 2026John ChiangNewtonProximal Gradient Descent

  42. Heterogeneity-Aware Personalized Federated Learning for Industrial Predictive Analytics

    Apr 21, 2026Yuhan Hu, Xiaolei FangHeterogeneous Federated LearningPredictive Maintenance

  43. Robust Tangent Space Estimation via Laplacian Eigenvector Gradient Orthogonalization

    Oct 2, 2025Dhruv Kohli, Sawyer J. Robertson, Gal Mishne +1Tangent SpaceProximal Gradient Descent

  44. Deep learning methods for inverse problems using connections between proximal operators and Hamilton-Jacobi equations

    Date pendingOluwatosin Akande, Gabriel P. Langlois, Akwum OnwuntaIll-Posed Inverse ProblemInverse Problem