Stochastic Gradient Descent

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  1. Learning Gaussian Structure: Intervention-Guided Density Control for Feed-Forward Driving Reconstruction

    Aug 11, 2026Hang Li, Jiahe Li, Meiying Gu +3Lidar3D Gaussian Splatting

  2. Efficient Hypergradient Descent for Inverse Reinforcement Learning

    Aug 11, 2026Nikita Sevriukov, Anna Barabanova, Uliana Gagarina +4Entropy Regularized Reinforcement LearningGradient Descent

  3. Can Bayesian Optimization Efficiently Find a Strong Single Expert in Neural Thickets?

    Aug 11, 2026Nigel Bastian Cendra, Abdelhamid Ezzerg, Fernando Julio Cendra +2Gradient-Based OptimizationBayesian Optimization

  4. A lower bound for stepsize-based acceleration of gradient descent

    Aug 11, 2026Jianhao Ma, Yuxin ChenLarge Step SizesGradient Descent

  5. Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks

    Aug 10, 2026Binchuan QiGradient DescentConvex Sets

  6. Why Post-Norm Transformers Collapse: Attention Amplification and Gradient Repair Failure

    Aug 10, 2026Xingjian Wang, Qingyu Han, Xiaodong Luo +1Batch NormalizationTransformer Encoder

  7. Adaptive Hybrid Particle Swarm Optimization with Gradient Descent

    Aug 7, 2026Aryan GurudeoParticle Swarm OptimizationGradient Descent

  8. Flow-Corrected Shape Optimization: Taming Manifold Drift in High-Dimensional 3D Models

    Aug 7, 2026Emilien Seiler, Nicolas Talabot, Yingxuan You +2Information-Geometric Optimization3D Models

  9. Stochastic gradient descent with discontinuity across a manifold

    Aug 7, 2026Vivek S. BorkarStochastic Gradient DescentManifolds

  10. Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification

    Aug 6, 2026Alex Buna, Shirley Xiaoqi Liu, Patrick RebeschiniEmpirical Risk MinimizationGaussian Mixture Models

  11. Continual Learning in Transition

    Aug 6, 2026Zhiyan Hou, Dan Zhang, Tao Feng +11Continual Learning MethodsTransitions

  12. GROM: Gradient-Free Rapid One-Shot Machine Unlearning

    Aug 6, 2026Paweł Batorski, Przemysław Spurek, Paul SwobodaGradient-Based OptimizationRegularization Techniques

  13. LC-Implicit-QAOA: Active-Workspace-Capped Exact Objective-and-Gradient Evaluation for Training over Bounded QUBO Light Cones

    Aug 6, 2026Chih-Chung HsuQuantum Approximate Optimization AlgorithmBilevel Optimization

  14. The Loss Does Not See the Basis, but Adam Does

    Aug 5, 2026Devender SinghLow-Rank FactorizationAdam

  15. On MUON optimization: From non-convergence to an error analysis with Polar Express and the Newton-Schulz polynomial from implementations

    Aug 5, 2026Thang Do, Steffen Dereich, Arnulf JentzenMuon OptimizerStochastic Gradient Descent

  16. Non-asymptotic implicit bias of logistic regression at early-stage gradient descent dynamics

    Aug 5, 2026Han BaoGradient DescentOver-Parameterized Neural Networks

  17. A Spectral Filtering Approach to Regret Analysis of Distributed Online Control for Linear Dynamical Systems

    Aug 3, 2026Ting-Jui ChangLinear Quadratic RegulatorGradient Descent

  18. AOS: Adaptive Optimizer Switching via Training-State Signals for Faster Convergence and Better Generalization

    Aug 3, 2026Alok Kumar Pandey, Umang Chaturvedi, Aatish Rana +1Neural Network OptimizationLearning Rates

  19. Not the Dimension, the Norm: What Matters in Gradient-Free Weight Perturbation of Language Models

    Aug 3, 2026Taeyeong Kim, Ahhyun Kim, TaeHyeon Kim +1Model WeightsGradient-Based Optimization

  20. One-Sided Quantile Coupling for Flow Matching

    Aug 2, 2026Jin-Young Kim, So-Yoon Cho, Hyun-Gyoon KimGenerative ModelsMini-Batch Stochastic Gradient Descent

  21. Adaptivity via a Parallel Architecture for Stochastic Gradient Methods

    Jul 31, 2026Bin FuStochastic Gradient DescentGradient Descent

  22. SDO: Structure-Aware Data Organization for Efficient LLM Post-Training

    Jul 29, 2026Jinliang Gao, Ning Yang, Hai Wang +2LLM Post-Training MethodsMini-Batch Stochastic Gradient Descent

  23. Simultaneous Coverage and Efficiency Guarantee in Online Conformal Prediction

    Jul 29, 2026Rahul VazeFinite-Sample Coverage GuaranteesConformal Inference

  24. Adaptive Gradient-Based Methods for a Broader Class of Optimization Problems under Performative Prediction

    Jul 29, 2026Hiroki Hamaguchi, Yuya Hikima, Hiroshi Sawada +1Gradient-Based OptimizationLoss Function

  25. Quotient Dynamics, Effective Curvature, and Implicit Bias in Positive Quadratic Networks

    Jul 28, 2026Pengcheng ChengCurvatureWasserstein Gradient Flows

  26. Data-Dependent Regret and Polyak Corrections for Constrained Online Convex Optimization

    Jul 28, 2026Wentao ZhangConvex OptimizationO(T^Β)$ Simultaneous Regret

  27. Extracting Voice Styles from Frozen TTS Models via Gradient-Based Inverse Optimization

    Jul 28, 2026Gyeongmin KimZero-Shot Text-To-SpeechWav2Vec

  28. Global Convergence of DGM and PINN Algorithms for Solving Nonlinear PDEs

    Jul 27, 2026Justin Sirignano, Konstantinos Spiliopoulos, Samuel CohenPartial Differential Equation BenchmarksPartial Differential Equations

  29. Mechanisms of Width Scaling in Normalized Residual Networks: The Effective Alignment Dimension

    Jul 27, 2026Jinhao Zhang, Zeyu Liu, Zicheng Yan +4Residual ConnectionsResidual Learning

  30. Greedy dynamical meta-learning

    Jul 27, 2026Aria YomMeta-LearningGradient-Based Optimization

  31. A Trust-region Framework for Moment Estimation

    Jul 26, 2026Oluwasegun A. SomefunTrust RegionStochastic Gradient Descent

  32. Latent-LoRA: Compact Latent-Space Adapters with Gradient-Free Routing for Continual Learning

    Jul 26, 2026Reza Rahimi Azghan, Gautham Krishna Gudur, Giulia Pedrielli +2Efficient Continual LearningLow-Rank Adaptation Adapters

  33. DP-IVON-Gradsq: Differentially Private Squared-Gradient Improved Variational Online Newton

    Jul 26, 2026Nour Jamoussi, Ikram Dridi, Giuseppe Serra +1Differential PrivacyStochastic Gradient Descent

  34. Sparse Gaussian-Mixture-Model Q-Functions via Hadamard Overparametrization for Online Reinforcement Learning

    Jul 26, 2026Minh Vu, Konstantinos SlavakisOffline Reinforcement LearningRiemannian Optimization

  35. Mini-batch Noise Lowers Sharpness via Dominant-Subspace Fluctuations

    Jul 25, 2026Junho So, Dongwook ShinMini-Batch Stochastic Gradient DescentSharpness-Aware Minimization

  36. Learning from the Descent Direction: Adaptive Gradient Descent under One-Sided Hölder Regularity

    Jul 24, 2026Arzu Ahmadova, Ismail HuseynovGradient DescentDescent

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

    Jul 24, 2026Peng ZhaoRegularization TechniquesQuadratic Slack Penalty

  38. Complexity Bounds and Approaches to Learning Projected Gradient Descent Solver Iterates

    Jul 24, 2026Anjian Li, Ryne BeesonGradient DescentNewton

  39. Energy Manifold Natural Gradient Descent: Riemannian Optimization for Neural PDE Solvers

    Jul 24, 2026Zhangyong Liang, Huanhuan GaoNeural Partial Differential Equation SolversRiemannian Optimization

  40. From Perturbation Correction to Geometry-Aware Sampling: Sharpness-Guided Equilibrium Sampling for Balanced Flat Minima in Long-Tailed Learning

    Jul 24, 2026Jiaxin Deng, Junbiao PangSharpness-Aware MinimizationBalanced Learning

  41. Gradient Concentration, Not Weight Saliency, Explains Representation-Level Class Unlearning

    Jul 23, 2026Billel Habbati, Alessio Merlo, Luca Verderame +1Several Approximate Unlearning StrategiesCatastrophic Forgetting

  42. Information-Theoretically Secure Aggregation for Lightweight Federated Learning: Resilient to Dropouts and Adversaries

    Jul 23, 2026Hyeong-Gun Joo, Songnam Hong, Dong-Joon ShinFederated LearningHomomorphic Encryption

  43. GaugeQuant: Online Learning of Quantization-Optimal Bases from LLM Symmetries

    Jul 22, 2026Miguel P. Bento, João F. SeabraW4A4 QuantizationGauge

  44. An Isotropy-Preserving Spectral Cap for Muon: Theory and Three Case Studies

    Jul 22, 2026Jiachun LiMuonModel Weights

  45. RELTA-SGLD: Relative-Growth Localized Taming for Nonconvex Stochastic-Gradient Langevin Learning

    Jul 21, 2026Yiwei Zhou, Ziheng ChenStochastic Gradient DescentNonconvex

  46. 1-Lipschitz Neural Networks on Hadamard Manifolds

    Jul 21, 2026Davide Murari, Marta Ghirardelli, Ben Adcock +3Lipschitz ConstantNeural Network

  47. Optimizing Regret

    Jul 21, 2026Irene AldridgeRegretGradient Descent

  48. Enhanced Neural Quantum State via Annealed Gradient Descent

    Jul 21, 2026Shiwei Zhou, Yiming Huang, Xiao Yuan +1Quantum Neural NetworksMany-Body Physics

  49. PRIME: Plasticity Recovery in Multi-Agent Environments for UAV-Assisted Emergency Communication Networks

    Jul 20, 2026Wen Qiu, Zhiqiang He, Wei Zhao +1Multi-Agent Reinforcement LearningPlasticity

  50. Backpropagation-Free Trunk Training via the Split Forward Gradients

    Jul 18, 2026Tian Qin, Wei-Min HuangBackpropagationGradient Flow

  51. Exact Network Surgery: Functional Invariance and Gradient Plasticity in Reactive Computational Graphs

    Jul 18, 2026Abdallah KhemaisResidual ConnectionsGradient Descent

  52. Scaling Limits of Constant-Stepsize SGD at Flat Minima

    Jul 17, 2026Jingyi Zhang, Cheng Mao, Debankur MukherjeeLarge Step SizesStochastic Gradient Descent

  53. Explaining Process Control Optimisation Recommendations via GradientSHAP and Implicit Differentiation

    Jul 16, 2026Paul Darm, Cem Alpturk, Kenneth Ulrich +3Shapley ValuePrompt Optimization

  54. What's in a Smoothness Constant? Tighter Rates for Local SGD with Bounded Second-order Heterogeneity

    Jul 16, 2026Kumar Kshitij Patel, Rustem Islamov, Sebastian U Stich +3Stochastic Gradient DescentSmoothing

  55. Grad2Fair: A Gradient-driven Approach for Graph Fairness without Demographics

    Jul 16, 2026Yuchang Zhu, Zezhong Xie, Huizhe Zhang +4Fairness-Aware LearningFederated Graph Learning

  56. TCAM-Diff: Triplane-Aware Cross-Attention Medical Diffusion Model

    Jul 15, 2026Zhenkai Zhang, Krista A. Ehinger, Tom Drummond3D Latent Diffusion ModelMedical Image Generation

  57. Approximation of solutions of parameter-dependent problems by residual neural networks

    Jul 15, 2026Ana CarpioNeural-Network ApproximationNeural Network

  58. Gradient-free learning of a closed-loop wall controller for turbulent drag reduction

    Jul 14, 2026Giorgio Maria Cavallazzi, Miguel Pérez Cuadrado, Alfredo PinelliTurbulenceClosed-Loop Control

  59. Environment Parameter Gradient Theorem for Policy-Environment Co-Design in Reinforcement Learning

    Jul 14, 2026Amber SrivastavaValue FunctionsGradient Flow

  60. Same Loss, Same Noise, Opposite Schedules: Noise Structure and Optimizer Normalization Jointly Determine Whether Learning-Rate Cooldown Helps

    Jul 14, 2026Subham Singh, Ashutosh Mishra, Subha RautLearning RatesStochastic Gradient Descent