7 citations · 19 across the 10 of their papers we have counts for
13 papers
Fast Block Linear System Solver Using Q-Learning Schduling for Unified Dynamic Power System Simulations
Yingshi Chen, Xinli Song, HanYang Dai +3
We present a fast block direct solver for the unified dynamic simulations of power systems. This solver uses a novel Q-learning based method for task scheduling. Unified dynamic si…
Learning the Markov Decision Process in the Sparse Gaussian Elimination
Yingshi Chen
We propose a learning-based approach for the sparse Gaussian Elimination. There are many hard combinatorial optimization problems in modern sparse solver. These NP-hard problems co…
The Brownian motion in the transformer model
Yingshi Chen
Transformer is the state of the art model for many language and visual tasks. In this paper, we give a deep analysis of its multi-head self-attention (MHSA) module and find that: 1…
An iterative K-FAC algorithm for Deep Learning
Yingshi Chen
Kronecker-factored Approximate Curvature (K-FAC) method is a high efficiency second order optimizer for the deep learning. Its training time is less than SGD(or other first-order m…
A short note on the decision tree based neural turing machine
Yingshi Chen
Turing machine and decision tree have developed independently for a long time. With the recent development of differentiable models, there is an intersection between them. Neural t…
Attention augmented differentiable forest for tabular data
Yingshi Chen
Differentiable forest is an ensemble of decision trees with full differentiability. Its simple tree structure is easy to use and explain. With full differentiability, it would be t…