Search Results for author: Changwei Hu

Found 13 papers, 0 papers with code

TNT: Text Normalization based Pre-training of Transformers for Content Moderation

no code implementations EMNLP 2020 Fei Tan, Yifan Hu, Changwei Hu, Keqian Li, Kevin Yen

In this work, we present a new language pre-training model TNT (Text Normalization based pre-training of Transformers) for content moderation.

BERT-Beta: A Proactive Probabilistic Approach to Text Moderation

no code implementations EMNLP 2021 Fei Tan, Yifan Hu, Kevin Yen, Changwei Hu

Text moderation for user generated content, which helps to promote healthy interaction among users, has been widely studied and many machine learning models have been proposed.

regression

TSI: an Ad Text Strength Indicator using Text-to-CTR and Semantic-Ad-Similarity

no code implementations18 Aug 2021 Shaunak Mishra, Changwei Hu, Manisha Verma, Kevin Yen, Yifan Hu, Maxim Sviridenko

To realize this opportunity, we propose an ad text strength indicator (TSI) which: (i) predicts the click-through-rate (CTR) for an input ad text, (ii) fetches similar existing ads to create a neighborhood around the input ad, (iii) and compares the predicted CTRs in the neighborhood to declare whether the input ad is strong or weak.

Click-Through Rate Prediction Retrieval +2

Political Posters Identification with Appearance-Text Fusion

no code implementations19 Dec 2020 Xuan Qin, Meizhu Liu, Yifan Hu, Christina Moo, Christian M. Riblet, Changwei Hu, Kevin Yen, Haibin Ling

In this paper, we propose a method that efficiently utilizes appearance features and text vectors to accurately classify political posters from other similar political images.

HABERTOR: An Efficient and Effective Deep Hatespeech Detector

no code implementations EMNLP 2020 Thanh Tran, Yifan Hu, Changwei Hu, Kevin Yen, Fei Tan, Kyumin Lee, Serim Park

HABERTOR inherits BERT's architecture, but is different in four aspects: (i) it generates its own vocabularies and is pre-trained from the scratch using the largest scale hatespeech dataset; (ii) it consists of Quaternion-based factorized components, resulting in a much smaller number of parameters, faster training and inferencing, as well as less memory usage; (iii) it uses our proposed multi-source ensemble heads with a pooling layer for separate input sources, to further enhance its effectiveness; and (iv) it uses a regularized adversarial training with our proposed fine-grained and adaptive noise magnitude to enhance its robustness.

Large-scale Gender/Age Prediction of Tumblr Users

no code implementations2 Jan 2020 Yao Zhan, Changwei Hu, Yifan Hu, Tejaswi Kasturi, Shanmugam Ramasamy, Matt Gillingham, Keith Yamamoto

In this paper, we propose graph based and deep learning models for age and gender predictions, which take into account user activities and content features.

Network Embedding

A Deep Structural Model for Analyzing Correlated Multivariate Time Series

no code implementations2 Jan 2020 Changwei Hu, Yifan Hu, Sungyong Seo

The seasonality component is approximated via a non-liner function of a set of Fourier terms, and the event components are learned by a simple linear function of regressor encoding the event dates.

Time Series Time Series Analysis

Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors

no code implementations18 Aug 2015 Changwei Hu, Piyush Rai, Lawrence Carin

We present a scalable Bayesian model for low-rank factorization of massive tensors with binary observations.

Bayesian Inference

Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data

no code implementations18 Aug 2015 Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin

We present a Bayesian non-negative tensor factorization model for count-valued tensor data, and develop scalable inference algorithms (both batch and online) for dealing with massive tensors.

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