Convergence Analysis

Ask about this field

Recent momentum

emerging

0 papers in the last 28 days · 0.0% of indexed attention

Twelve weeks of publication activity for this topic as it is defined today.

Weekly history

Recent digests

What was published in this field, kept on the site without email delivery.

Period ending 2026-09-21

9 new papers

A weekly snapshot of new work published in Convergence Analysis.

Period ending 2026-09-14

5 new papers

A weekly snapshot of new work published in Convergence Analysis.

Period ending 2026-09-07

2 new papers

A weekly snapshot of new work published in Convergence Analysis.

Inside this field

Focused directions

229 papers

Latest in Convergence Analysis

Browse all topics →
CardsList

  1. Silent Failures in Quantized LLM Reasoning: A Taxonomy-Based Analysis of Hollow Convergence and Failure Mode Shifts

    Jul 10, 2026Renuka Oladri, Mohan Vamsi Varadaraju Priya, Jerry WuLarge Language Model QuantizationLarge Language Model Performance

  2. Understanding Schedule-Free Methods in Nonconvex Optimization: Rate Guarantees and Escaping Saddles

    Jul 10, 2026Jiseok Chae, Donghwan KimConvex OptimizationConvergence Analysis

  3. Vanilla SGD with Momentum Survives Heavy-Tailed Noise: Convergence Analysis without Gradient Clipping or Normalization

    Jul 9, 2026Ryusei Yamada, Naoki Sato, Hideaki IidukaStochastic Gradient DescentConvergence Analysis

  4. Near-Optimal Learning of Gaussian Sobolev Operators

    Jul 8, 2026Ben Adcock, Michael Griebel, Gregor MaierLogarithmic Sobolev InequalitiesProbabilistic Operator Learning

  5. Optimal Learning Rate Scaling Depends on Data in Deep Scalar Linear Networks

    Jul 8, 2026Yedi Zhang, Peter E. Latham, Leena Chennuru Vankadara +1Learning RatesScaling Laws

  6. Mathematical methods of reinforcement learning

    Jul 8, 2026Denis Belomestny, Alexander Gasnikov, Egor Gladin +5Entropy Regularized Reinforcement LearningMarkov Decision Processes

  7. On the convergence of graph Laplacians with a symmetric divergence

    Jul 7, 2026Liane XuGraph LaplaciansRiemannian Manifolds

  8. Non-asymptotic Convergence of Stochastic Gradient Descent in Score-based Generative Models

    Jul 6, 2026Stanislas Strasman, Sobihan Surendran, Sylvain Le CorffStochastic Gradient DescentGenerative Models

  9. Trust Region Policy Distillation

    Jul 6, 2026Zhengpeng Xie, Li Lyna Zhang, Zeke Xie +1On-Policy DistillationConvergence Analysis

  10. Unified convergence analysis for gradient descent optimization methods in the training of deep neural networks

    Jul 5, 2026Shokhrukh Ibragimov, Arnulf JentzenNeural Network OptimizationAdam

  11. Knowing When to Stop: Predicting Execution-Consistency Convergence in Text-to-SQL

    Jul 4, 2026Yaron Anavi, Mor Aisenberg, Nadav Nesher +2Text-To-SqlSql

  12. On the Convergence of Adam, Revisited

    Jul 3, 2026Steven Heilman, Sampad MohantyAdamFederated Averaging

  13. Statistical Properties of kk-means Clustering for Data Missing Completely at Random

    Jul 2, 2026Xin GuanK-MeansCluster Structure

  14. Decentralized Stochastic Subgradient-type Methods with Communication Compression for Nonsmooth Nonconvex Optimization

    Jul 2, 2026Siyuan Zhang, Nachuan Xiao, Xin LiuStochastic Smooth Convex OptimizationConvex Optimization

  15. Random Reshuffling Dominates Stochastic Gradient Descent

    Jun 30, 2026Zijian LiuStochastic Gradient DescentConvergence Analysis

  16. On the Convergence of Self-Improving Online LLM Alignment

    Jun 30, 2026Xudong Wu, Pangpang Liu, Vaneet Aggarwal +1Large Language Model AlignmentUnsupervised On-Policy Self-Distillation

  17. Convergence of Continual Learning in Homogeneous Deep Networks

    Jun 29, 2026Matan Schliserman, Gon Buzaglo, Itay Evron +1Efficient Continual LearningSingular Learning Theory

  18. ManimAgent: Self-Evolving Multimodal Agents for Visual Education

    Jun 29, 2026Wenjia Jiang, Zongyuan Cai, Yuanhang Shao +7Multimodal AgentsCode Generation

  19. Federated Learning with Energy-Based Structured Probabilistic Inference

    Jun 29, 2026Dario Fenoglio, Daniil Kirilenko, Martin Gjoreski +1Federated LearningDistributional Learning

  20. SP-CACW: Convergence-Aware Client Weighting for Selfish Personalized Learning

    Jun 28, 2026Yaron Kiselman, Kfir Y. LevyFederated LearningWeighted

  21. Analysis of Parameter Settings for the Bat Algorithm Using Variance Evolution

    Jun 26, 2026Xin-She Yang, Mehmet KaramanogluEvolutionary SearchBandits

  22. A Fast Convergent Algorithm for Solving Non-convex Partially-Decoupled Generalized Nash Equilibrium Problems

    Jun 26, 2026Bennet Outland, Vishala AryaZero--Sum Differential GameNash Equilibrium

  23. Diffusion Models Adapt to Low-Dimensional Structure Under Flexible Coefficient Choices

    Jun 22, 2026Changxiao Cai, Yuchen Jiao, Gen LiDiffusion SamplingLow-Dimensional Structure

  24. Convergence of Gradient Descent for General Neural Network Architectures Beyond the NTK Regime

    Jun 22, 2026Yuqing WangNeural Tangent KernelGradient Descent

  25. Non-asymptotic estimates of the minimal risk in statistical learning

    Jun 22, 2026Liming Wu, Sen YangEmpirical Risk MinimizationConcentration Inequalities

  26. Generalized nonparametric regression in reproducing kernel Hilbert spaces: Consistency and rates of convergence

    Jun 22, 2026Ioannis KalogridisKernel Hilbert SpacesEstimators

  27. GARIP: A Running-Average Moving Reference for Last-Iterate Self-Play in Two-Player Zero-Sum Games

    Jun 21, 2026Can SavcıSelf-PlayConvergence Analysis

  28. Distribution-Aware Robust Bilevel Optimization: Quantile-Guided Huber Updates in Two-Timescale Stochastic Approximation

    Jun 21, 2026Zhiyu Li, Xi Xuan, Davide CarboneBilevel OptimizationStochastic Approximation

  29. Escaping the Variance Trap: Jacobian-Free Dynamics for Root-Finding Bilevel Optimization

    Jun 21, 2026Zhiyu Li, Xi Xuan, Davide CarboneBilevel OptimizationStochastic Approximation

  30. Adam Converges in Nonsmooth Nonconvex Optimization

    Jun 21, 2026Zijian LiuAdamConvex Optimization

  31. Convergence Analysis of Nyström Subsampling in Covariate Shift Adaptation for Misspecified case

    Jun 20, 2026Hanna Myleiko, Sergei Solodky, Vasyl SemenovDomain AdaptationCovariate Shift

  32. Accelerated and Stable Convergence with Anchored Optimistic Method

    Jun 19, 2026Motahareh Sohrabi, Jianxin You, Simon Lacoste-Julien +2Convergence AnalysisFlat Minima

  33. Central limit theorem for the averaged Adam optimizer

    Jun 19, 2026Steffen Dereich, Arnulf JentzenCentral Limit TheoremStochastic Approximation

  34. Global Convergence of Gradient Descent for Score Matching in Gaussian Mixtures via Reverse Fisher Divergence

    Jun 18, 2026Alexander TyurinGaussian Mixture ModelsGradient Descent

  35. Semiglobal Input-Delay Tolerance Algorithm for Distributed Nonconvex Optimization of Networked Nonlinear Systems

    Jun 18, 2026Jing-Zhe Xu, Zhi-Wei Liu, Ming-Feng Ge +2Convex OptimizationConvergence Analysis

  36. CREDENCE: Claim Reduction for Decomposition & Enhanced Credibility -- Semantic Metrics and Convergence Analysis

    Jun 18, 2026Phuong Huu Vu Tran, Thuan Duc Mai, Bach Xuan LeFact-CheckingEntailment

  37. A Diffusion Approximation for Temporal-Difference Learning with Linear Features under Markovian Noise

    Jun 16, 2026M. Forzo, E. Monzio Compagnoni, A. Russo +1Temporal DifferenceStochastic Approximation

  38. Beyond IGO-Flow: Toward Convergence Analysis of IGO in Continuous Spaces

    Jun 16, 2026Ryosuke Kimura, Youhei AkimotoInformation-Geometric OptimizationConvergence Analysis

  39. Contrastive-Difference CKA Reveals Concept-Specific Structural Alignment Across Language Model Architectures

    Jun 15, 2026Xueping GaoCross-Architecture GeneralizationLarge Language Model Alignment

  40. Scalar-Stepsize Nonuniform Monte Carlo Optimistic Policy Iteration: A Certified Counterexample

    Jun 14, 2026Yuanlong ChenStochastic ApproximationOptimal Policies

  41. SILAGE: Memory-Efficient, Full-Gradient-Free Nonconvex Optimization for Nested Finite Sums

    Jun 14, 2026Igor Sokolov, Laurent Condat, Peter RichtárikVariance ReductionConvergence Analysis

  42. Nonlinear Two-Time-Scale Stochastic Approximation: A Sharp Phase Transition and How to Beat It

    Jun 12, 2026Dhruv Sarkar, Vaneet AggarwalStochastic ApproximationFinite Time Analysis

  43. Operator Calculus for Population-Based Optimization: A Mean-Field Convergence Theory

    Jun 12, 2026Pekka Malo, Lauri Viitasaari, Patrik Nummi +3Mean-Field LimitLyapunov Function

  44. Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers

    Jun 11, 2026Samuel Erickson, Mikael JohanssonStochastic Gradient DescentGradient Clipping

  45. Last-Iterate Convergence of Optimistic Multiplicative Weight Update

    Jun 10, 2026Francesco OrabonaConvex OptimizationConvergence

  46. Limitations of Learning Tanh Neural Networks with Finite Precision

    Jun 9, 2026Philipp Grohs, Matěj TrödlerNeural NetworkFull-Precision Performance

  47. From Data Heterogeneity to Convergence: A Data-Centric Review of Federated Learning

    Jun 9, 2026Huong Nguyen, Mickaël Bettinelli, Amirhossein Ghaffari +4Federated LearningHeterogeneity

  48. Convergence of Monte Carlo Optimistic Policy Iteration: Beyond Uniform State-Action Updates

    Jun 9, 2026Octave Oliviers, Glenn VinnicombeOptimal PoliciesMonte Carlo

  49. Near-Exponential Convergence Rates for kNN Classification based on Boltzmann Margin

    Jun 9, 2026Luyuan Yang, Shayan Shafaei, Chao LanApproximate Nearest-Neighbor SearchConvergence Analysis

  50. Improved Convergence Analysis of Topology Dependence in Decentralized SGD

    Jun 8, 2026Yuki Takezawa, Anastasia Koloskova, Sebastian U. StichConvergence AnalysisStochastic Gradient Descent

  51. Instrumental convergence and power-seeking

    Jun 7, 2026David ThorstadArtificial Intelligence AgentsHuman Oversight

  52. Fast and Robust Convergence Rate for TD(0) with Linear Function Approximation, Universal Learning Steps and I.I.D. Samples

    Jun 4, 2026Ziad Kobeissi, Éloïse BerthierTemporal DifferenceFinite Time Analysis

  53. Mitigating the Curse of Dimensionality in Uniform Convergence of Deep Neural Networks via Smooth Activations

    Jun 4, 2026Yizhe Ding, Runze Li, Jia Liu +1Rectified Linear Unit NetworksActivation Functions

  54. Near-Optimal Decentralized Stochastic Convex Optimization over Networks

    Jun 3, 2026Nitai Kluger, Amit Attia, Tomer KorenStochastic Smooth Convex OptimizationStochastic Approximation

  55. Analytical Evaluation of DCA Convergence Properties for Minimizing Prediction Functions of Gaussian RBF Support Vector Regression

    Jun 2, 2026Yohei Kakimoto, Yuto Omae, Hirotaka TakahashiConvex OptimizationRadial Basis Function

  56. Adaptive Sharpness-Aware Minimization with a Polyak-type Step size: A Theory-Grounded Scheduler

    Jun 1, 2026Dimitris Oikonomou, Nicolas LoizouStochastic Gradient DescentSharpness-Aware Minimization

  57. Global Convergence of a Line-Search Filter Differential Dynamic Programming Method

    May 31, 2026Ming Xu, Iman ShamesOptimal ControlInequality Constraints

  58. Theoretical Analysis of Engression and Reverse Markov Engression

    May 31, 2026Jiaqi Huang, Gongjun Xu, Ji ZhuFinite Time AnalysisTheoretical Foundations

  59. Not All Flips Are Conformity: Decomposing Stance Convergence in Multi-Agent LLM Debate

    May 30, 2026Xiqi Hao, Zengqing Wu, Yu-Xuan Qiu +4Multi-Agent DebateDebate

  60. Balanced LoRA: Removing Parameter Invariance to Accelerate Convergence

    May 29, 2026Valérie Castin, Kimia Nadjahi, Pierre Ablin +1Low-Rank AdaptationFinetuning