53 citations · 81 across the 10 of their papers we have counts for
10 papers
Labeled Subgraph Entropy Kernel
Chengyu Sun, Xing Ai, Zhihong Zhang +1
In recent years, kernel methods are widespread in tasks of similarity measuring. Specifically, graph kernels are widely used in fields of bioinformatics, chemistry and financial da…
PA-GM: Position-Aware Learning of Embedding Networks for Deep Graph Matching
Dongdong Chen, Yuxing Dai, Lichi Zhang +1
Graph matching can be formalized as a combinatorial optimization problem, where there are corresponding relationships between pairs of nodes that can be represented as edges. This…
Two-level Graph Neural Network
Xing Ai, Chengyu Sun, Zhihong Zhang +1
Graph Neural Networks (GNNs) are recently proposed neural network structures for the processing of graph-structured data. Due to their employed neighbor aggregation strategy, exist…
Towards Quantum Graph Neural Networks: An Ego-Graph Learning Approach
Xing Ai, Zhihong Zhang, Luzhe Sun +2
Quantum machine learning is a fast-emerging field that aims to tackle machine learning using quantum algorithms and quantum computing. Due to the lack of physical qubits and an eff…
DLA-Net: Learning Dual Local Attention Features for Semantic Segmentation of Large-Scale Building Facade Point Clouds
Yanfei Su, Weiquan Liu, Zhimin Yuan +4
Semantic segmentation of building facade is significant in various applications, such as urban building reconstruction and damage assessment. As there is a lack of 3D point clouds…
Feature refinement: An expression-specific feature learning and fusion method for micro-expression recognition
Ling Zhou, Qirong Mao, Xiaohua Huang +2
Micro-Expression Recognition has become challenging, as it is extremely difficult to extract the subtle facial changes of micro-expressions. Recently, several approaches proposed s…
Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis
Lu Bai, Lixin Cui, Lixiang Xu +3
In this work, we develop a novel framework to measure the similarity between dynamic financial networks, i.e., time-varying financial networks. Particularly, we explore whether the…
Identifying The Most Informative Features Using A Structurally Interacting Elastic Net
Lixin Cui, Lu Bai, Zhihong Zhang +2
Feature selection can efficiently identify the most informative features with respect to the target feature used in training. However, state-of-the-art vector-based methods are una…
Deep Stock Representation Learning: From Candlestick Charts to Investment Decisions
Guosheng Hu, Yuxin Hu, Kai Yang +8
We propose a novel investment decision strategy (IDS) based on deep learning. The performance of many IDSs is affected by stock similarity. Most existing stock similarity measureme…
A Boosting Method to Face Image Super-resolution
Shanjun Mao, Da Zhou, Yiping Zhang +2
Recently sparse representation has gained great success in face image super-resolution. The conventional sparsity-based methods enforce sparse coding on face image patches and the…