Cluster-Based Cooperative Digital Over-the-Air Aggregation for Wireless Federated Edge Learning. - Ruichen Jiang; Sheng Zhou 001 (ICCC, 2020)

Achieving Cooperative Diversity in Over-the-Air Computation via Relay Selection. - Ruichen Jiang; Sheng Zhou 001; Kaibin Huang (VTC Fall, 2020)

Antenna Efficiency in Massive MIMO Detection. - Ruichen Jiang; Ya-Feng Liu (SPAWC, 2021)

Tightness and Equivalence of Semidefinite Relaxations for MIMO Detection. - Ruichen Jiang; Ya-Feng Liu; Chenglong Bao; Bo Jiang 010 (CoRR, 2021)

Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems. - Mao Ye 006; Ruichen Jiang; Haoxiang Wang 003; Dhruv Choudhary; Xiaocong Du; Bhargav Bhushanam; Aryan Mokhtari; Arun Kejariwal; Qiang Liu 001 (UAI, 2022)

Generalized Optimistic Methods for Convex-Concave Saddle Point Problems. - Ruichen Jiang; Aryan Mokhtari (CoRR, 2022)

Generalized Frank-Wolfe Algorithm for Bilevel Optimization. - Ruichen Jiang; Nazanin Abolfazli; Aryan Mokhtari; Erfan Yazdandoost Hamedani (CoRR, 2022)

A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem. - Ruichen Jiang; Nazanin Abolfazli; Aryan Mokhtari; Erfan Yazdandoost Hamedani (AISTATS, 2023)

Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergence. - Ruichen Jiang; Qiujiang Jin; Aryan Mokhtari (COLT, 2023)

Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem. - Jincheng Cao; Ruichen Jiang; Nazanin Abolfazli; Erfan Yazdandoost Hamedani; Aryan Mokhtari (NeurIPS, 2023)

Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization. - Ruichen Jiang; Aryan Mokhtari (NeurIPS, 2023)

Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate. - Ruichen Jiang; Parameswaran Raman; Shoham Sabach; Aryan Mokhtari; Mingyi Hong 001; Volkan Cevher (AISTATS, 2024)

An Accelerated Gradient Method for Convex Smooth Simple Bilevel Optimization. - Jincheng Cao; Ruichen Jiang; Erfan Yazdandoost Hamedani; Aryan Mokhtari (NeurIPS, 2024)

Stochastic Newton Proximal Extragradient Method. - Ruichen Jiang; Michal Derezinski; Aryan Mokhtari (NeurIPS, 2024)

Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization. - Ruichen Jiang; Ali Kavis; Qiujiang Jin; Sujay Sanghavi; Aryan Mokhtari (NeurIPS, 2024)

Non-asymptotic Global Convergence Analysis of BFGS with the Armijo-Wolfe Line Search. - Qiujiang Jin; Ruichen Jiang; Aryan Mokhtari (NeurIPS, 2024)

An Accelerated Gradient Method for Simple Bilevel Optimization with Convex Lower-level Problem. - Jincheng Cao; Ruichen Jiang; Erfan Yazdandoost Hamedani; Aryan Mokhtari (CoRR, 2024)

Convergence Analysis of Adaptive Gradient Methods under Refined Smoothness and Noise Assumptions. - Devyani Maladkar; Ruichen Jiang; Aryan Mokhtari (CoRR, 2024)

Online Learning Guided Quasi-Newton Methods with Global Non-Asymptotic Convergence. - Ruichen Jiang; Aryan Mokhtari (CoRR, 2024)

Provable Complexity Improvement of AdaGrad over SGD: Upper and Lower Bounds in Stochastic Non-Convex Optimization. - Ruichen Jiang; Devyani Maladkar; Aryan Mokhtari (COLT, 2025)

Improved Complexity for Smooth Nonconvex Optimization: A Two-Level Online Learning Approach with Quasi-Newton Methods. - Ruichen Jiang; Aryan Mokhtari; Francisco Patitucci (STOC, 2025)

Online Learning-guided Learning Rate Adaptation via Gradient Alignment. - Ruichen Jiang; Ali Kavis; Aryan Mokhtari (CoRR, 2025)

On the Complexity of Finding Stationary Points in Nonconvex Simple Bilevel Optimization. - Jincheng Cao; Ruichen Jiang; Erfan Yazdandoost Hamedani; Aryan Mokhtari (CoRR, 2025)