23 citations · 84 across the 8 of their papers we have counts for
8 papers
Beyond Backpropagation: Monte Carlo Method Can Train Deep Neural Networks
Hong Zhao
Backpropagation (BP) dominates deep learning training, but its reliance on gradients brings inherent troubles -- vanishing and exploding gradients. The pursuit of gradient-free met…
How and what to learn:The modes of machine learning
Sihan Feng, Yong Zhang, Fuming Wang +1
Despite their great success, neural networks still remain as black-boxes due to the lack of interpretability. Here we propose a new analyzing method, namely the weight pathway anal…
Inferring Global Dynamics Using a Learning Machine
Hong Zhao
Given a segment of time series of a system at a particular set of parameter values, can one infers the global behavior of the system in its parameter space? Here we show that by us…
Inferring Global Dynamics of a Black-Box System Using Machine Learning
Hong Zhao
We present that, instead of establishing the equations of motion, one can model-freely reveal the dynamical properties of a black-box system using a learning machine. Trained only…
Copy the dynamics using a learning machine
Hong Zhao
Is it possible to generally construct a dynamical system to simulate a black system without recovering the equations of motion of the latter? Here we show that this goal can be app…
A General Theory for Training Learning Machine
Hong Zhao
Though the deep learning is pushing the machine learning to a new stage, basic theories of machine learning are still limited. The principle of learning, the role of the a prior kn…