Mingrui Liu

Tight Bounds for Logistic Regression with Large Stepsize Gradient Descent in Low Dimension COLT 2026 Complexity Lower Bounds of Adaptive Gradient Algorithms for Non-convex Stochastic Optimization under Relaxed Smoothness ICLR 2025 Constant Stepsize Local GD for Logistic Regression: Acceleration by Instability ICML 2025 Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression ICLR 2025 Algorithmic Foundation of Federated Learning with Sequential Data AAAI 2024 An Accelerated Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness NeurIPS 2024 A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness ICML 2024 Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis ICLR 2024 Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis NeurIPS 2024 Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective ICML 2024 AUC Maximization in Imbalanced Lifelong Learning UAI 2023 Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm NeurIPS 2023 EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data ICLR 2023 Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds NeurIPS 2023 Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization NeurIPS 2023 A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks NeurIPS 2022 Fast Composite Optimization and Statistical Recovery in Federated Learning ICML 2022 On the Initialization for Convex-Concave Min-max Problems ALT 2022 On the Last Iterate Convergence of Momentum Methods ALT 2022 Robustness to Unbounded Smoothness of Generalized SignSGD NeurIPS 2022 Will Bilevel Optimizers Benefit from Loops NeurIPS 2022 First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems JMLR 2021 Generalization Guarantee of SGD for Pairwise Learning NeurIPS 2021 A Decentralized Parallel Algorithm for Training Generative Adversarial Nets NeurIPS 2020 Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks ICML 2020 Improved Schemes for Episodic Memory-based Lifelong Learning NeurIPS 2020 Stochastic AUC Maximization with Deep Neural Networks ICLR 2020 Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets ICLR 2020 Adaptive Negative Curvature Descent with Applications in Non-convex Optimization NeurIPS 2018 Faster Online Learning of Optimal Threshold for Consistent F-measure Optimization NeurIPS 2018 Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions NeurIPS 2018 Fast Stochastic AUC Maximization with $O(1/n)$-Convergence Rate ICML 2018 Adaptive Accelerated Gradient Converging Method under H\"{o}lderian Error Bound Condition NeurIPS 2017 ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive Penalization NeurIPS 2017