Search Results for author: Yanghui Rao

Found 10 papers, 6 papers with code

Nonparametric Forest-Structured Neural Topic Modeling

2 code implementations COLING 2022 Zhihong Zhang, Xuewen Zhang, Yanghui Rao

Neural topic models have been widely used in discovering the latent semantics from a corpus.

Topic Models

Topic Driven Adaptive Network for Cross-Domain Sentiment Classification

no code implementations28 Nov 2021 Yicheng Zhu, Yiqiao Qiu, Qingyuan Wu, Fu Lee Wang, Yanghui Rao

In this vein, most approaches utilized domain adaptation that maps data from different domains into a common feature space.

Classification Domain Adaptation +3

Tree-Structured Topic Modeling with Nonparametric Neural Variational Inference

1 code implementation ACL 2021 Ziye Chen, Cheng Ding, Zusheng Zhang, Yanghui Rao, Haoran Xie

Topic modeling has been widely used for discovering the latent semantic structure of documents, but most existing methods learn topics with a flat structure.

Variational Inference

Target-specified Sequence Labeling with Multi-head Self-attention for Target-oriented Opinion Words Extraction

1 code implementation NAACL 2021 Yuhao Feng, Yanghui Rao, Yuyao Tang, Ninghua Wang, He Liu

Many recent works on ABSA focus on Target-oriented Opinion Words (or Terms) Extraction (TOWE), which aims at extracting the corresponding opinion words for a given opinion target.

Aspect-Based Sentiment Analysis (ABSA) Language Modelling +2

Context Reinforced Neural Topic Modeling over Short Texts

1 code implementation11 Aug 2020 Jiachun Feng, Zusheng Zhang, Cheng Ding, Yanghui Rao, Haoran Xie

As one of the prevalent topic mining tools, neural topic modeling has attracted a lot of interests for the advantages of high efficiency in training and strong generalisation abilities.

text-classification Topic Models +1

Neural Mixed Counting Models for Dispersed Topic Discovery

no code implementations ACL 2020 Jiemin Wu, Yanghui Rao, Zusheng Zhang, Haoran Xie, Qing Li, Fu Lee Wang, Ziye Chen

Mixed counting models that use the negative binomial distribution as the prior can well model over-dispersed and hierarchically dependent random variables; thus they have attracted much attention in mining dispersed document topics.

Variational Inference

Siamese Network-Based Supervised Topic Modeling

no code implementations EMNLP 2018 Minghui Huang, Yanghui Rao, Yuwei Liu, Haoran Xie, Fu Lee Wang

Label-specific topics can be widely used for supporting personality psychology, aspect-level sentiment analysis, and cross-domain sentiment classification.

General Classification Sentiment Analysis +3

A Network Framework for Noisy Label Aggregation in Social Media

no code implementations ACL 2017 Xueying Zhan, Yao-Wei Wang, Yanghui Rao, Haoran Xie, Qing Li, Fu Lee Wang, Tak-Lam Wong

This paper focuses on the task of noisy label aggregation in social media, where users with different social or culture backgrounds may annotate invalid or malicious tags for documents.

Cultural Vocal Bursts Intensity Prediction Image Classification +2

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