{"total":38,"rows":[{"id":"2102.10346","title":"Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance","created":"2021-02-20","cited_by_count":35,"area":null},{"id":"2106.14352","title":"Instance-optimality in optimal value estimation: Adaptivity via variance-reduced Q-learning","created":"2021-06-28","cited_by_count":22,"area":null},{"id":"2108.02391","title":"Adapting to Function Difficulty and Growth Conditions in Private Optimization","created":"2021-08-05","cited_by_count":20,"area":null},{"id":"2302.07690","title":"Online Statistical Inference for Nonlinear Stochastic Approximation with Markovian Data","created":"2023-02-15","cited_by_count":20,"area":null},{"id":"2304.06833","title":"Estimate-Then-Optimize versus Integrated-Estimation-Optimization versus Sample Average Approximation: A Stochastic Dominance Perspective","created":"2023-04-13","cited_by_count":20,"area":null},{"id":"2201.08518","title":"Optimal variance-reduced stochastic approximation in Banach spaces","created":"2022-01-21","cited_by_count":17,"area":null},{"id":"2102.03389","title":"Online Statistical Inference for Stochastic Optimization via Kiefer-Wolfowitz Methods","created":"2021-02-05","cited_by_count":14,"area":null},{"id":"2301.06632","title":"Asymptotic normality and optimality in nonsmooth stochastic approximation","created":"2023-01-16","cited_by_count":14,"area":null},{"id":"2207.04173","title":"Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality","created":"2022-07-09","cited_by_count":12,"area":null},{"id":"2205.13687","title":"Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming","created":"2022-05-27","cited_by_count":10,"area":null},{"id":"2401.09346","title":"High Confidence Level Inference is Almost Free using Parallel Stochastic Optimization","created":"2024-01-17","cited_by_count":10,"area":null},{"id":"2212.14883","title":"Online Statistical Inference for Contextual Bandits via Stochastic Gradient Descent","created":"2022-12-30","cited_by_count":8,"area":null},{"id":"2112.02612","title":"Training Structured Neural Networks Through Manifold Identification and Variance Reduction","created":"2021-12-05","cited_by_count":7,"area":null},{"id":"2308.01481","title":"Online covariance estimation for stochastic gradient descent under Markovian sampling","created":"2023-08-03","cited_by_count":7,"area":null},{"id":"2102.05198","title":"Statistical Inference for Polyak-Ruppert Averaged Zeroth-order Stochastic Gradient Algorithm","created":"2021-02-10","cited_by_count":6,"area":null},{"id":"2304.00707","title":"High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance","created":"2023-04-03","cited_by_count":6,"area":null},{"id":"2305.05828","title":"A Normal Map-Based Proximal Stochastic Gradient Method: Convergence and Identification Properties","created":"2023-05-10","cited_by_count":5,"area":null},{"id":"2111.15645","title":"Survey Descent: A Multipoint Generalization of Gradient Descent for Nonsmooth Optimization","created":"2021-11-30","cited_by_count":4,"area":null},{"id":"2304.13950","title":"Fairness Uncertainty Quantification: How certain are you that the model is fair?","created":"2023-04-27","cited_by_count":4,"area":null},{"id":"2306.10081","title":"Optimizer's Information Criterion: Dissecting and Correcting Bias in Data-Driven Optimization","created":"2023-06-16","cited_by_count":4,"area":null},{"id":"2402.07131","title":"Resampling methods for private statistical inference","created":"2024-02-11","cited_by_count":4,"area":null},{"id":"2502.05305","title":"Online Covariance Estimation in Nonsmooth Stochastic Approximation","created":"2025-02-07","cited_by_count":4,"area":null},{"id":"2512.13123","title":"Stopping Rules for Stochastic Gradient Descent via Anytime-Valid Confidence Sequences","created":"2025-12-15","cited_by_count":4,"area":null},{"id":"2510.18215","title":"The Bias-Variance Tradeoff in Data-Driven Optimization: A Local Misspecification Perspective","created":"2025-10-21","cited_by_count":3,"area":null},{"id":"2504.03560","title":"Stochastic Optimization with Optimal Importance Sampling","created":"2025-04-04","cited_by_count":2,"area":null},{"id":"2505.17300","title":"Statistical Inference for Online Algorithms","created":"2025-05-22","cited_by_count":2,"area":null},{"id":"2101.05234","title":"On Misspecification in Prediction Problems and Robustness via Improper Learning","created":"2021-01-13","cited_by_count":1,"area":null},{"id":"2106.02713","title":"Learning Curves for SGD on Structured Features","created":"2021-06-04","cited_by_count":1,"area":null},{"id":"2208.13701","title":"Data-Driven Influence Functions for Optimization-Based Causal Inference","created":"2022-08-29","cited_by_count":1,"area":null},{"id":"2302.09727","title":"Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression","created":"2023-02-20","cited_by_count":1,"area":null},{"id":"2404.00042","title":"Stochastic Optimization with Constraints: A Non-asymptotic Instance-Dependent Analysis","created":"2024-03-24","cited_by_count":1,"area":null},{"id":"2405.09676","title":"The radius of statistical efficiency","created":"2024-05-15","cited_by_count":1,"area":null},{"id":"2510.19734","title":"Statistical Inference for Linear Functionals of Online Least-squares SGD when $t \\gtrsim d^{1+\\delta}$","created":"2025-10-22","cited_by_count":1,"area":null},{"id":"2208.07243","title":"Exponential Concentration in Stochastic Approximation","created":"2022-08-15","cited_by_count":0,"area":null},{"id":"2407.10955","title":"Enhancing Stochastic Optimization for Statistical Efficiency Using ROOT-SGD with Diminishing Stepsize","created":"2024-07-15","cited_by_count":0,"area":null},{"id":"2505.18327","title":"Online Statistical Inference of Constrained Stochastic Optimization via Random Scaling","created":"2025-05-23","cited_by_count":0,"area":null},{"id":"2605.24274","title":"A lift for input-convex neural net training","created":"2026-05-22","cited_by_count":0,"area":null},{"id":"2609.37425","title":"A stochastic subgradient method with optimal failure exponent","created":"2026-09-29","cited_by_count":0,"area":null}],"next_cursor":null}