16 citations · 37 across the 9 of their papers we have counts for
9 papers
Dizygotic Conditional Variational AutoEncoder for Multi-Modal and Partial Modality Absent Few-Shot Learning
Yi Zhang, Sheng Huang, Xi Peng +1
Data augmentation is a powerful technique for improving the performance of the few-shot classification task. It generates more samples as supplements, and then this task can be tra…
Plot2API: Recommending Graphic API from Plot via Semantic Parsing Guided Neural Network
Zeyu Wang, Sheng Huang, Zhongxin Liu +4
Plot-based Graphic API recommendation (Plot2API) is an unstudied but meaningful issue, which has several important applications in the context of software engineering and data visu…
Regression-based Hypergraph Learning for Image Clustering and Classification
Sheng Huang, Dan Yang, Bo Liu +1
Inspired by the recently remarkable successes of Sparse Representation (SR), Collaborative Representation (CR) and sparse graph, we present a novel hypergraph model named Regressio…
Learning Hypergraph-regularized Attribute Predictors
Sheng Huang, Mohamed Elhoseiny, Ahmed Elgammal +1
We present a novel attribute learning framework named Hypergraph-based Attribute Predictor (HAP). In HAP, a hypergraph is leveraged to depict the attribute relations in the data. T…
On The Effect of Hyperedge Weights On Hypergraph Learning
Sheng Huang, Ahmed Elgammal, Dan Yang
Hypergraph is a powerful representation in several computer vision, machine learning and pattern recognition problems. In the last decade, many researchers have been keen to develo…
Sparse Graph-based Transduction for Image Classification
Sheng Huang, Dan Yang, Jia Zhou +2
Motivated by the remarkable successes of Graph-based Transduction (GT) and Sparse Representation (SR), we present a novel Classifier named Sparse Graph-based Classifier (SGC) for i…