Stochastic Gradient Descent

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Period ending 2026-09-21

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  1. Gradient-Discrepancy Acquisition for Pool-Based Active Learning

    May 4, 2026Mohamadsadegh Khosravani, Sandra ZillesActive LearningGradient-Based Optimization

  2. Universal Smoothness via Bernstein Polynomials: A Constructive Approximation Approach for Activation Functions

    May 4, 2026Wentao Zhang, Yutong Zhang, Yifan Zhu +1Activation FunctionsSmoothing

  3. Anon: Extrapolating Adaptivity Beyond SGD and Adam

    May 4, 2026Yiheng Zhang, Kaiyan Zhao, Shaowu Wu +5AdamParameter-Efficient Adaptation

  4. Bringing Order to Asynchronous SGD: Towards Optimality under Data-Dependent Delays with Momentum

    May 3, 2026Tehila Dahan, Roie Reshef, Sharon Goldstein +1Stochastic Gradient DescentLearning Rates

  5. Training Non-Differentiable Networks via Optimal Transport

    May 3, 2026An T. LeGradient-Based OptimizationBackpropagation

  6. Finite-Size Gradient Transport in Large Language Model Pretraining: From Cascade Size to Intensive Transport Efficiency

    May 3, 2026Ping Wang, Yan-Qi DuLarge ModelsLarge Language Model Pretraining

  7. Stability and Generalization for Decentralized Markov SGD

    May 3, 2026Jiahuan Wang, Ziqing Wen, Ping Luo +2Stochastic Gradient DescentGeneralization Bounds

  8. A Theory of Generalization in Deep Learning

    May 2, 2026Elon Litman, Gabe GuoNeural Tangent KernelOver-Parameterized Neural Networks

  9. Reinforcement Learning with Markov Risk Measures and Multipattern Risk Approximation

    May 1, 2026Andrzej Ruszczynski, Tiangang ZhangQ-LearningMulti-Armed Bandits

  10. Bridging Graph Drawing and Dimensionality Reduction with Stochastic Stress Optimization

    May 1, 2026Daniel Hangan, Stephen Kobourov, Jacob MillerDimensionality ReductionStochastic Gradient Descent

  11. Intrinsic Gradient Suppression for Label-Noise Prompt Tuning in Vision-Language Models

    May 1, 2026Jiayu Li, Jiaxin Qi, Sheng Zhou +2Prompt TuningZero-Shot Inference

  12. LambdaRankIC: Directly Optimizing Rank IC for Financial Prediction

    May 1, 2026Yan Lin, Yihong Su, Yi YangRankingGradient Flow

  13. Federated Learning with Hypergradient-based Online Update of Aggregation Weights

    May 1, 2026Ayano Nakai-Kasai, Tadashi WadayamaFederated LearningGradient Descent

  14. High-Probability Convergence in Decentralized Stochastic Optimization with Gradient Tracking

    Apr 30, 2026Aleksandar Armacki, Haoyuan Cai, Ali H. SayedStochastic Gradient DescentStochastic Optimization

  15. Cost-Aware Learning

    Apr 30, 2026Clara Mohri, Amir Globerson, Haim Kaplan +2Group Relative Policy OptimizationStochastic Gradient Descent

  16. Faster 3D Gaussian Splatting Convergence via Structure-Aware Densification

    Apr 30, 2026Linjie Lyu, Ayush Tewari, Jianchun Chen +23D Gaussian3D Gaussian Splatting

  17. Dynamic Scaled Gradient Descent for Stable Fine-Tuning for Classifications

    Apr 30, 2026Nghia Bui, Lijing WangGradient DescentClass Imbalance

  18. Attractor FCM

    Apr 30, 2026Alexis KafantarisAttractorsGradient Descent

  19. Information-Theoretic Generalization Bounds for Stochastic Gradient Descent with Predictable Virtual Noise

    Apr 30, 2026Mohammad PartohaghighiStochastic Gradient DescentGeneralization Bounds

  20. Learning Rate Engineering: From Coarse Single Parameter to Layered Evolution

    Apr 30, 2026Ming-Hong Yao, Di Wang, Jian Cui +5Learning RatesStochastic Gradient Descent

  21. Learning to Forget: Continual Learning with Adaptive Weight Decay

    Apr 29, 2026Aditya A. Ramesh, Alex Lewandowski, Jürgen SchmidhuberLearning RatesContinual Learning Methods

  22. Bi-Level Optimization for Contact and Motion Planning in Rope-Assisted Legged Robots

    Apr 29, 2026Ruben Malacarne, Ioannis Tsikelis, Enrico Mingo Hoffman +1TerrainRobot Systems

  23. Understanding DNNs in Feature Interaction Models: A Dimensional Collapse Perspective

    Apr 29, 2026Jiancheng Wang, Mingjia Yin, Hao Wang +1Higher-Order CorrelationsToward Interaction Dynamics

  24. State-Dependent Lyapunov Analysis of Rank-1 Matrix Factorization

    Apr 28, 2026Jaehong MoonMatrix FactorizationLyapunov Function

  25. Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane

    Apr 28, 2026Pahal D. Patel, Sanmay GangulyExplainabilityExplainable Artificial Intelligence

  26. Towards interpretable AI with quantum annealing feature selection

    Apr 28, 2026Francesco Aldo Venturelli, Emanuele Costa, Sikha O K +3Feature SelectionGradient Flow

  27. Adversarial Robustness of NTK Neural Networks

    Apr 28, 2026Yuxuan HouNeural Tangent KernelNeural Network

  28. Sliced-Regularized Optimal Transport

    Apr 27, 2026Khai NguyenOptimal TransportGradient Flow

  29. A Topology fixated Shape Gradient Framework for Non Simple Boundary Extraction for CIE Lab color images with Repulsive Energy

    Apr 25, 2026Shafeequdheen Palengara, Jyotiranjan Nayak, Vijayakrishna RowthuSharp Boundary DelineationRobust Segmentation

  30. Complex Stochastic Gradient Descent and Directional Bias in Reproducing Kernel Hilbert Spaces

    Apr 24, 2026Natanael Alpay, Emeric BattagliaKernel Hilbert SpacesStochastic Gradient Descent

  31. Separable Expert Architecture: Toward Privacy-Preserving LLM Personalization via Composable Adapters and Deletable User Proxies

    Apr 23, 2026Chris Schneider, Philipp Schoenegger, Ben BariachPersonalizationLow-Rank Adaptation Adapters

  32. Refining Covariance Matrix Estimation in Stochastic Gradient Descent Through Bias Reduction

    Apr 23, 2026Ziyang Wei, Wanrong Zhu, Jingyang Lyu +1Stochastic Gradient DescentCovariance Estimation

  33. SGD at the Edge of Stability: The Stochastic Sharpness Gap

    Apr 22, 2026Fangshuo Liao, Afroditi Kolomvaki, Anastasios KyrillidisStochastic Gradient DescentSharpness-Aware Minimization

  34. The Origin of Edge of Stability

    Apr 22, 2026Elon LitmanCondition NumberGradient Descent

  35. Properties and limitations of geometric tempering for gradient flow dynamics

    Apr 22, 2026Francesca Romana Crucinio, Sahani PathirajaWasserstein Gradient FlowsFisher Information

  36. Structure-Aware Variational Learning of a Class of Generalized Diffusions

    Apr 22, 2026Yubin Lu, Xiaofan Li, Chun Liu +2Stochastic Differential EquationsVariational

  37. Machine learning moment closure models for the radiative transfer equation IV: enforcing symmetrizable hyperbolicity in two dimensions

    Apr 22, 2026Juntao HuangHyperbolic SpaceClosure

  38. Efficient Reinforcement Learning using Linear Koopman Dynamics for Nonlinear Robotic Systems

    Apr 21, 2026Wenjian Hao, Yuxuan Fang, Zehui Lu +1Koopman OperatorDeep Reinforcement Learning

  39. FedSEA: Achieving Benefit of Parallelization in Federated Online Learning

    Apr 21, 2026Harekrushna Sahu, Pratik Jawanpuria, Pranay SharmaFederated LearningFederated Reinforcement Learning

  40. Intentional Updates for Streaming Reinforcement Learning

    Apr 21, 2026Arsalan Sharifnassab, Mohamed Elsayed, Kris De Asis +2Policy GradientDeep Reinforcement Learning

  41. FG2^2-GDN: Enhancing Long-Context Gated Delta Networks with Doubly Fine-Grained Control

    Apr 21, 2026Pingwei Sun, Yuxuan Hu, Jianchao Tan +6Global Attention MechanismEfficient Long-Context Inference

  42. Random Matrix Theory of Early-Stopped Gradient Flow: A Transient BBP Scenario

    Apr 20, 2026Florentin Coeurdoux, Grégoire Ferré, Jean-Philippe BouchaudGradient FlowGradient Descent

  43. Centre manifold theorem for maps along manifolds of fixed points

    Apr 20, 2026Lachlan Ewen MacDonaldManifoldsGradient Descent

  44. Compiling Deterministic Structure into SLM Harnesses

    Apr 19, 2026Zan Kai Chong, Hiroyuki Ohsaki, Bryan NgSmall Language ModelsDeterministic

  45. Decomposing the Depth Profile of Fine-Tuning

    Apr 19, 2026Jayadev BillaGradient FlowTransformer Layers

  46. Lower Bounds and Proximally Anchored SGD for Non-Convex Minimization Under Unbounded Variance

    Apr 17, 2026Arda Fazla, Ege C. Kaya, Antesh Upadhyay +1Stochastic Smooth Convex OptimizationStochastic Gradient Descent

  47. Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation

    Apr 17, 2026Yide Ran, Jianwen Xie, Minghui Wang +4Training Data AttributionReadout

  48. Adapting in the Dark: Efficient and Stable Test-Time Adaptation for Black-Box Models

    Apr 17, 2026Yunbei Zhang, Shuaicheng Niu, Chengyi Cai +2Stable Test-Time AdaptationReal-Time Inference

  49. Natural gradient descent with momentum

    Apr 16, 2026Anthony Nouy, Agustín SomacalGradient DescentLoss Function

  50. Optimizing Stochastic Gradient Push under Broadcast Communications

    Apr 16, 2026Tuan Nguyen, Ting HeStochastic Gradient DescentWireless Resource Allocation

  51. StoSignSGD: Unbiased Structural Stochasticity Fixes SignSGD for Training Large Language Models

    Apr 16, 2026Dingzhi Yu, Rui Pan, Yuxing Liu +1Stochastic Gradient DescentOptimizer Design

  52. Wasserstein Formulation of Reinforcement Learning. An Optimal Transport Perspective on Policy Optimization

    Apr 16, 2026Mathias DusRiemannian OptimizationWasserstein Distance

  53. Stochastic-Dimension Frozen Sampled Neural Network for High-Dimensional Gross-Pitaevskii Equations on Unbounded Domains

    Apr 10, 2026Zhangyong Liang, Huanhuan GaoNeural Partial Differential Equation SolversGradient-Based Optimization

  54. Marginal-Contribution Policy Gradients under Filtered Feedback for Multi-Agent LLMs

    Apr 3, 2026Elai Ben-Gal, Stela TongCredit AssignmentMulti-Agent Reinforcement Learning

  55. Critical Damping as a Momentum Schedule: Multi-Seed Validation, a Hybrid Recipe, and an Exhaustive Negative Result on Surgical Layer Selection

    Mar 30, 2026Ivan PasichnykStochastic Gradient DescentVisual Attribution

  56. Uniform a priori bounds and error analysis for the Adam stochastic gradient descent optimization method

    Mar 19, 2026Steffen Dereich, Thang Do, Arnulf JentzenAdamStochastic Smooth Convex Optimization

  57. DISCOVER: A Solver for Distributional Counterfactual Explanations

    Mar 17, 2026Yikai Gu, Lele Cao, Bo Zhao +2Counterfactual ExplanationCounterfactual Reasoning

  58. Dataset Distillation Efficiently Encodes Low-Dimensional Representations from Gradient-Based Learning of Non-Linear Tasks

    Mar 16, 2026Yuri Kinoshita, Naoki Nishikawa, Taro ToyoizumiLow-Dimensional StructureContext Compression

  59. First-Order Softmax Weighted Switching Gradient Method for Distributed Stochastic Minimax Optimization with Stochastic Constraints

    Mar 6, 2026Zhankun Luo, Antesh Upadhyay, Sang Bin Moon +1Stochastic OptimizationFederated Learning

  60. Non-Euclidean Gradient Descent Operates at the Edge of Stability

    Mar 5, 2026Rustem Islamov, Michael Crawshaw, Jeremy Cohen +1Gradient DescentSharpness-Aware Minimization