164 citations · 412 across the 9 of their papers we have counts for
9 papers
SpellGCN: Incorporating Phonological and Visual Similarities into Language Models for Chinese Spelling Check
Xingyi Cheng, Weidi Xu, Kunlong Chen +5
Chinese Spelling Check (CSC) is a task to detect and correct spelling errors in Chinese natural language. Existing methods have made attempts to incorporate the similarity knowledg…
BERT-Based Multi-Head Selection for Joint Entity-Relation Extraction
Weipeng Huang, Xingyi Cheng, Taifeng Wang +1
In this paper, we report our method for the Information Extraction task in 2019 Language and Intelligence Challenge. We incorporate BERT into the multi-head selection framework for…
Symmetric Regularization based BERT for Pair-wise Semantic Reasoning
Weidi Xu, Xingyi Cheng, Kunlong Chen +7
The ability of semantic reasoning over the sentence pair is essential for many natural language understanding tasks, e.g., natural language inference and machine reading comprehens…
Toward Fast and Accurate Neural Chinese Word Segmentation with Multi-Criteria Learning
Weipeng Huang, Xingyi Cheng, Kunlong Chen +2
The ambiguous annotation criteria lead to divergence of Chinese Word Segmentation (CWS) datasets in various granularities. Multi-criteria Chinese word segmentation aims to capture…
Variational Semi-supervised Aspect-term Sentiment Analysis via Transformer
Xingyi Cheng, Weidi Xu, Taifeng Wang +1
Aspect-term sentiment analysis (ATSA) is a longstanding challenge in natural language understanding. It requires fine-grained semantical reasoning about a target entity appeared in…
Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers
Quanming Yao, James T. Kwok, Taifeng Wang +1
Low-rank modeling has many important applications in computer vision and machine learning. While the matrix rank is often approximated by the convex nuclear norm, the use of noncon…
Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction
Qi Meng, Wei Chen, Jingcheng Yu +3
Regularized empirical risk minimization (R-ERM) is an important branch of machine learning, since it constrains the capacity of the hypothesis space and guarantees the generalizati…
Asynchronous Stochastic Gradient Descent with Delay Compensation
Shuxin Zheng, Qi Meng, Taifeng Wang +4
With the fast development of deep learning, it has become common to learn big neural networks using massive training data. Asynchronous Stochastic Gradient Descent (ASGD) is widely…
Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks
Yuyu Zhang, Hanjun Dai, Chang Xu +5
Click prediction is one of the fundamental problems in sponsored search. Most of existing studies took advantage of machine learning approaches to predict ad click for each event o…