Ruichen Jiang

According to our database, Ruichen Jiang authored at least 17 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Online Learning Guided Quasi-Newton Methods with Global Non-Asymptotic Convergence.

Ruichen Jiang, Aryan Mokhtari

CoRR, 2024

Convergence Analysis of Adaptive Gradient Methods under Refined Smoothness and Noise Assumptions.

Devyani Maladkar, Ruichen Jiang, Aryan Mokhtari

CoRR, 2024

Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization.

Ruichen Jiang, Ali Kavis, Qiujiang Jin, Sujay Sanghavi, Aryan Mokhtari

CoRR, 2024

Stochastic Newton Proximal Extragradient Method.

Ruichen Jiang, Michal Derezinski, Aryan Mokhtari

CoRR, 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

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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization.

Ruichen Jiang, Aryan Mokhtari

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergence.

Ruichen Jiang, Qiujiang Jin, Aryan Mokhtari

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem.

Ruichen Jiang, Nazanin Abolfazli, Aryan Mokhtari, Erfan Yazdandoost Hamedani

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Generalized Frank-Wolfe Algorithm for Bilevel Optimization.

Ruichen Jiang, Nazanin Abolfazli, Aryan Mokhtari, Erfan Yazdandoost Hamedani

CoRR, 2022

Generalized Optimistic Methods for Convex-Concave Saddle Point Problems.

Ruichen Jiang, Aryan Mokhtari

CoRR, 2022

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

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Tightness and Equivalence of Semidefinite Relaxations for MIMO Detection.

Ruichen Jiang, Ya-Feng Liu, Chenglong Bao, Bo Jiang

CoRR, 2021

Antenna Efficiency in Massive MIMO Detection.

Ruichen Jiang, Ya-Feng Liu

Proceedings of the 22nd IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2021

2020

Achieving Cooperative Diversity in Over-the-Air Computation via Relay Selection.

Ruichen Jiang, Sheng Zhou, Kaibin Huang

Proceedings of the 92nd IEEE Vehicular Technology Conference, 2020

Cluster-Based Cooperative Digital Over-the-Air Aggregation for Wireless Federated Edge Learning.

Ruichen Jiang, Sheng Zhou

Proceedings of the 9th IEEE/CIC International Conference on Communications in China, 2020