Jinyang Jiang

According to our database, Jinyang Jiang authored at least 16 papers between 2022 and 2025.

Collaborative distances:

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

2025

Forward Learning with Differential Privacy.

Mingqian Feng, Zeliang Zhang, Jinyang Jiang, Yijie Peng, Chenliang Xu

CoRR, April, 2025

CoNNect: A Swiss-Army-Knife Regularizer for Pruning of Neural Networks.

Christian Franssen, Jinyang Jiang, Yijie Peng, Bernd Heidergott

CoRR, February, 2025

Integrated Offline and Online Learning to Solve a Large Class of Scheduling Problems.

Anbang Liu, Zhi-Long Chen, Jinyang Jiang, Xi Chen

CoRR, January, 2025

Noise Optimization in Artificial Neural Networks.

Li Xiao, Zeliang Zhang, Kuihua Huang, Jinyang Jiang, Yijie Peng

IEEE Trans Autom. Sci. Eng., 2025

FLOPS: Forward Learning with OPtimal Sampling.

Tao Ren, Zishi Zhang, Jinyang Jiang, Guanghao Li, Zeliang Zhang, Mingqian Feng, Yijie Peng

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

A Parameter-Efficient Quantum Anomaly Detection Method on a Superconducting Quantum Processor.

Maida Wang, Jinyang Jiang, Peter V. Coveney

CoRR, 2024

Approximated Likelihood Ratio: A Forward-Only and Parallel Framework for Boosting Neural Network Training.

Zeliang Zhang, Jinyang Jiang, Zhuo Liu, Susan Liang, Yijie Peng, Chenliang Xu

CoRR, 2024

Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode.

Jinyang Jiang, Xiaotian Liu, Tao Ren, Qinghao Wang, Yi Zheng, Yufu Du, Yijie Peng, Cheng Zhang

CoRR, 2024

Distortion Risk Measure-Based Deep Reinforcement Learning.

Jinyang Jiang, Bernd Heidergott, Jiaqiao Hu, Yijie Peng

Proceedings of the Winter Simulation Conference, 2024

One Forward is Enough for Neural Network Training via Likelihood Ratio Method.

Jinyang Jiang, Zeliang Zhang, Chenliang Xu, Zhaofei Yu, Yijie Peng

Proceedings of the Twelfth International Conference on Learning Representations, 2024

RiskMiner: Discovering Formulaic Alphas via Risk Seeking Monte Carlo Tree Search.

Tao Ren, Ruihan Zhou, Jinyang Jiang, Jiafeng Liang, Qinghao Wang, Yijie Peng

Proceedings of the 5th ACM International Conference on AI in Finance, 2024

2023

Training Neural Networks without Backpropagation: A Deeper Dive into the Likelihood Ratio Method.

Jinyang Jiang, Zeliang Zhang, Chenliang Xu, Zhaofei Yu, Yijie Peng

CoRR, 2023

Quantile-Based Deep Reinforcement Learning using Two-Timescale Policy Gradient Algorithms.

Jinyang Jiang, Jiaqiao Hu, Yijie Peng

CoRR, 2023

A Novel Noise Injection-based Training Scheme for Better Model Robustness.

Zeliang Zhang, Jinyang Jiang, Minjie Chen, Zhiyuan Wang, Yijie Peng, Zhaofei Yu

CoRR, 2023

2022

Quantile-Based Policy Optimization for Reinforcement Learning.

Jinyang Jiang, Yijie Peng, Jiaqiao Hu

Proceedings of the Winter Simulation Conference, 2022

Noise Optimization in Artificial Neural Networks.

Li Xiao, Zeliang Zhang, Jinyang Jiang, Yijie Peng

Proceedings of the 18th IEEE International Conference on Automation Science and Engineering, 2022