activity
20152021
most citedCausality-based Feature Selection: Methods and Evaluations

28 citations · 68 across the 4 of their papers we have counts for

collaborators

8 papers

cs.LG202124 cited

Towards Efficient Local Causal Structure Learning

Shuai Yang, Hao Wang, Kui Yu +2

Local causal structure learning aims to discover and distinguish direct causes (parents) and direct effects (children) of a variable of interest from data. While emerging successes…

cs.CL2020

Chinese Lexical Simplification

Jipeng Qiang, Xinyu Lu, Yun Li +3

Lexical simplification has attracted much attention in many languages, which is the process of replacing complex words in a given sentence with simpler alternatives of equivalent m…

cs.CL202015 cited

LSBert: A Simple Framework for Lexical Simplification

Jipeng Qiang, Yun Li, Yi Zhu +2

Lexical simplification (LS) aims to replace complex words in a given sentence with their simpler alternatives of equivalent meaning, to simplify the sentence. Recently unsupervised…

cs.LG201928 cited

Causality-based Feature Selection: Methods and Evaluations

Kui Yu, Xianjie Guo, Lin Liu +4

Feature selection is a crucial preprocessing step in data analytics and machine learning. Classical feature selection algorithms select features based on the correlations between p…

cs.CL2019

Lexical Simplification with Pretrained Encoders

Jipeng Qiang, Yun Li, Yi Zhu +2

Lexical simplification (LS) aims to replace complex words in a given sentence with their simpler alternatives of equivalent meaning. Recently unsupervised lexical simplification ap…

cs.IR2018

STTM: A Tool for Short Text Topic Modeling

Jipeng Qiang, Yun Li, Yunhao Yuan +2

Along with the emergence and popularity of social communications on the Internet, topic discovery from short texts becomes fundamental to many applications that require semantic un…