3 citations · 4 across the 4 of their papers we have counts for
4 papers
Approximated Likelihood Ratio: A Forward-Only and Parallel Framework for Boosting Neural Network Training
Zeliang Zhang, Jinyang Jiang, Zhuo Liu +3
Efficient and biologically plausible alternatives to backpropagation in neural network training remain a challenge due to issues such as high computational complexity and additiona…
RiskMiner: Discovering Formulaic Alphas via Risk Seeking Monte Carlo Tree Search
Tao Ren, Ruihan Zhou, Jinyang Jiang +3
The formulaic alphas are mathematical formulas that transform raw stock data into indicated signals. In the industry, a collection of formulaic alphas is combined to enhance modeli…
Quantile-Based Deep Reinforcement Learning using Two-Timescale Policy Gradient Algorithms
Jinyang Jiang, Jiaqiao Hu, Yijie Peng
Classical reinforcement learning (RL) aims to optimize the expected cumulative reward. In this work, we consider the RL setting where the goal is to optimize the quantile of the cu…
A Novel Noise Injection-based Training Scheme for Better Model Robustness
Zeliang Zhang, Jinyang Jiang, Minjie Chen +3
Noise injection-based method has been shown to be able to improve the robustness of artificial neural networks in previous work. In this work, we propose a novel noise injection-ba…