220 citations · 452 across the 40 of their papers we have counts for
8 papers · 1 filter
Stable and Compact Face Recognition via Unlabeled Data Driven Sparse Representation-Based Classification
Xiaohui Yang, Zheng Wang, Huan Wu +3
Sparse representation-based classification (SRC) has attracted much attention by casting the recognition problem as simple linear regression problem. SRC methods, however, still is…
Nonparametric Sparse Tensor Factorization with Hierarchical Gamma Processes
Conor Tillinghast, Zheng Wang, Shandian Zhe
We propose a nonparametric factorization approach for sparsely observed tensors. The sparsity does not mean zero-valued entries are massive or dominated. Rather, it implies the obs…
Spectrum Gaussian Processes Based On Tunable Basis Functions
Wenqi Fang, Guanlin Wu, Jingjing Li +3
Spectral approximation and variational inducing learning for the Gaussian process are two popular methods to reduce computational complexity. However, in previous research, those m…
Reinforcement Learning-based Dialogue Guided Event Extraction to Exploit Argument Relations
Qian Li, Hao Peng, Jianxin Li +5
Event extraction is a fundamental task for natural language processing. Finding the roles of event arguments like event participants is essential for event extraction. However, doi…
Federated Learning with Fair Averaging
Zheng Wang, Xiaoliang Fan, Jianzhong Qi +3
Fairness has emerged as a critical problem in federated learning (FL). In this work, we identify a cause of unfairness in FL -- conflicting gradients with large differences in the…
Expanding Semantic Knowledge for Zero-shot Graph Embedding
Zheng Wang, Ruihang Shao, Changping Wang +3
Zero-shot graph embedding is a major challenge for supervised graph learning. Although a recent method RECT has shown promising performance, its working mechanisms are not clear an…
Lightweight Image Super-Resolution with Multi-scale Feature Interaction Network
Zhengxue Wang, Guangwei Gao, Juncheng Li +2
Recently, the single image super-resolution (SISR) approaches with deep and complex convolutional neural network structures have achieved promising performance. However, those meth…
A Reinforcement Learning Based R-Tree for Spatial Data Indexing in Dynamic Environments
Tu Gu, Kaiyu Feng, Gao Cong +3
Learned indices have been proposed to replace classic index structures like B-Tree with machine learning (ML) models. They require to replace both the indices and query processing…