3 citations · 10 across the 17 of their papers we have counts for
6 papers · 1 filter
A Parameter-Efficient Quantum Anomaly Detection Method on a Superconducting Quantum Processor
Maida Wang, Jinyang Jiang, Peter V. Coveney
Quantum machine learning has gained attention for its potential to address computational challenges. However, whether those algorithms can effectively solve practical problems and…
FLOPS: Forward Learning with OPtimal Sampling
Tao Ren, Zishi Zhang, Jinyang Jiang +4
Given the limitations of backpropagation, perturbation-based gradient computation methods have recently gained focus for learning with only forward passes, also referred to as quer…
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…
Forward Learning for Gradient-based Black-box Saliency Map Generation
Zeliang Zhang, Mingqian Feng, Jinyang Jiang +3
Gradient-based saliency maps are widely used to explain deep neural network decisions. However, as models become deeper and more black-box, such as in closed-source APIs like ChatG…
Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode
Jinyang Jiang, Xiaotian Liu, Tao Ren +5
We introduce a deep reinforcement learning (DRL) approach for solving management problems including inventory management, dynamic pricing, and recommendation. This DRL approach has…
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…