{"total":32,"rows":[{"id":"2210.04994","title":"Sampling-based inference for large linear models, with application to linearised Laplace","created":"2022-10-10","cited_by_count":18,"area":null},{"id":"2401.00364","title":"Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise","created":"2023-12-31","cited_by_count":15,"area":null},{"id":"2103.06263","title":"Semi-Discrete Optimal Transport: Hardness, Regularization and Numerical Solution","created":"2021-03-10","cited_by_count":13,"area":null},{"id":"2305.13209","title":"Faster Differentially Private Convex Optimization via Second-Order Methods","created":"2023-05-22","cited_by_count":13,"area":null},{"id":"2306.11497","title":"Convergence and concentration properties of constant step-size SGD through Markov chains","created":"2023-06-20","cited_by_count":11,"area":null},{"id":"2502.13283","title":"Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression","created":"2025-02-18","cited_by_count":9,"area":null},{"id":"2410.01112","title":"Almost Free: Self-concordance in Natural Exponential Families and an Application to Bandits","created":"2024-10-01","cited_by_count":8,"area":null},{"id":"2303.01370","title":"Non asymptotic analysis of Adaptive stochastic gradient algorithms and applications","created":"2023-03-01","cited_by_count":7,"area":null},{"id":"2305.12056","title":"Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent","created":"2023-05-20","cited_by_count":6,"area":null},{"id":"2209.03447","title":"Blessing of Class Diversity in Pre-training","created":"2022-09-07","cited_by_count":4,"area":null},{"id":"2310.02941","title":"Hoeffding's Inequality for Markov Chains under Generalized Concentrability Condition","created":"2023-10-04","cited_by_count":3,"area":null},{"id":"2401.10923","title":"Online estimation of the inverse of the Hessian for stochastic optimization with application to universal stochastic Newton algorithms","created":"2024-01-15","cited_by_count":3,"area":null},{"id":"2403.02051","title":"Privacy of SGD under Gaussian or Heavy-Tailed Noise: Guarantees without Gradient Clipping","created":"2024-03-04","cited_by_count":3,"area":null},{"id":"2507.20403","title":"A General Framework for Estimating Preferences Using Response Time Data","created":"2025-07-27","cited_by_count":3,"area":null},{"id":"2110.14813","title":"Stable Anderson Acceleration for Deep Learning","created":"2021-10-26","cited_by_count":2,"area":null},{"id":"2602.10697","title":"Fast and Large-Scale Unbalanced Optimal Transport via its Semi-Dual and Adaptive Gradient Methods","created":"2026-02-11","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":"2101.12113","title":"Low Complexity Approximate Bayesian Logistic Regression for Sparse Online Learning","created":"2021-01-28","cited_by_count":1,"area":null},{"id":"2205.11033","title":"Augmented Newton Method for Optimization: Global Linear Rate and Momentum Interpretation","created":"2022-05-23","cited_by_count":1,"area":null},{"id":"2410.03760","title":"On the SAGA algorithm with decreasing step","created":"2024-10-02","cited_by_count":1,"area":null},{"id":"2411.12029","title":"On the Efficiency of ERM in Feature Learning","created":"2024-11-18","cited_by_count":1,"area":null},{"id":"2509.17815","title":"Global Optimization via Softmin Energy Minimization","created":"2025-09-22","cited_by_count":1,"area":null},{"id":"2603.20967","title":"Hard labels sampled from sparse targets mislead rotation invariant algorithms","created":"2026-03-21","cited_by_count":1,"area":null},{"id":"2302.00982","title":"Stochastic optimal transport in Banach Spaces for regularized estimation of multivariate quantiles","created":"2023-02-02","cited_by_count":0,"area":null},{"id":"2306.15848","title":"Ordering for Non-Replacement SGD","created":"2023-06-28","cited_by_count":0,"area":null},{"id":"2405.14459","title":"Semi-Discrete Optimal Transport: Nearly Minimax Estimation With Stochastic Gradient Descent and Adaptive Entropic Regularization","created":"2024-05-23","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":"2503.18190","title":"Quantile-Based Randomized Kaczmarz for Corrupted Tensor Linear Systems","created":"2025-03-23","cited_by_count":0,"area":null},{"id":"2503.19942","title":"A stochastic gradient descent algorithm with random search directions","created":"2025-03-25","cited_by_count":0,"area":null},{"id":"2510.25287","title":"Stochastic Optimization in Semi-Discrete Optimal Transport: Convergence Analysis and Minimax Rate","created":"2025-10-29","cited_by_count":0,"area":null},{"id":"2510.27340","title":"Decreasing Entropic Regularization Averaged Gradient for Semi-Discrete Optimal Transport","created":"2025-10-31","cited_by_count":0,"area":null},{"id":"2605.19641","title":"Increasing Missingness to Reduce Bias: Richardson-SGD with Missing Data","created":"2026-05-19","cited_by_count":0,"area":null}],"next_cursor":null}