| 2026 | COLT | Adaptive Matrix Online Learning through Smoothing with Guarantees for Nonsmooth Nonconvex Optimization. | Ruichen Jiang, Zakaria Mhammedi, Mehryar Mohri, Aryan Mokhtari |
| 2025 | COLT | Provable Complexity Improvement of AdaGrad over SGD: Upper and Lower Bounds in Stochastic Non-Convex Optimization. | Ruichen Jiang, Devyani Maladkar, Aryan Mokhtari |
| 2025 | STOC | Improved Complexity for Smooth Nonconvex Optimization: A Two-Level Online Learning Approach with Quasi-Newton Methods. | Ruichen Jiang, Aryan Mokhtari, Francisco Patitucci |
| 2024 | AISTATS | Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate. | Ruichen Jiang, Parameswaran Raman, Shoham Sabach, Aryan Mokhtari, Mingyi Hong, Volkan Cevher |
| 2023 | AISTATS | A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem. | Ruichen Jiang, Nazanin Abolfazli, Aryan Mokhtari, Erfan Yazdandoost Hamedani |
| 2023 | COLT | Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergence. | Ruichen Jiang, Qiujiang Jin, Aryan Mokhtari |
| 2022 | UAI | Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems. | Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu |
| 2020 | VTC | Achieving Cooperative Diversity in Over-the-Air Computation via Relay Selection. | Ruichen Jiang, Sheng Zhou, Kaibin Huang |