5 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CL2019★ 5 cited
A Causal Inference Method for Reducing Gender Bias in Word Embedding Relations
Zekun Yang, Juan Feng
Word embedding has become essential for natural language processing as it boosts empirical performances of various tasks. However, recent research discovers that gender bias is inc…
cs.CL2019
Causally Denoise Word Embeddings Using Half-Sibling Regression
Zekun Yang, Tianlin Liu
Distributional representations of words, also known as word vectors, have become crucial for modern natural language processing tasks due to their wide applications. Recently, a gr…
eess.SP2019
PReS: Power Peak Reduction by Real-time Scheduling for Urban Railway Transit
Zekun Yang, Yu Chen, Ning Zhou +1
Railway transportation is one of the most popular options for Urban Massive Transportation Systems (UMTS) because of many attractive features. A robust electric power supply is ess…