activity
20172020
most citedA concatenating framework of shortcut convolutional neural networks

8 citations · 9 across the 3 of their papers we have counts for

collaborators

6 papers

cs.LG2020

Probabilistic K-means Clustering via Nonlinear Programming

Yujian Li, Bowen Liu, Zhaoying Liu +1

K-means is a classical clustering algorithm with wide applications. However, soft K-means, or fuzzy c-means at m=1, remains unsolved since 1981. To address this challenging open pr…

cs.LG20191 cited

A Capsule-unified Framework of Deep Neural Networks for Graphical Programming

Yujian Li, Chuanhui Shan

Recently, the growth of deep learning has produced a large number of deep neural networks. How to describe these networks unifiedly is becoming an important issue. We first formali…

cs.LG2018

A Unified Framework of Deep Neural Networks by Capsules

Yujian Li, Chuanhui Shan

With the growth of deep learning, how to describe deep neural networks unifiedly is becoming an important issue. We first formalize neural networks mathematically with their direct…

cs.SE2018

Entropy Guided Spectrum Based Bug Localization Using Statistical Language Model

Saikat Chakraborty, Yujian Li, Matt Irvine +2

Locating bugs is challenging but one of the most important activities in software development and maintenance phase because there are no certain rules to identify all types of bugs…

cs.CV20178 cited

A concatenating framework of shortcut convolutional neural networks

Yujian Li, Ting Zhang, Zhaoying Liu +1

It is well accepted that convolutional neural networks play an important role in learning excellent features for image classification and recognition. However, in tradition they on…

cs.AI2017

Can Machines Think in Radio Language?

Yujian Li

People can think in auditory, visual and tactile forms of language, so can machines principally. But is it possible for them to think in radio language? According to a first princi…