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LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
- Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang, Meng Wang
- Computer ScienceSIGIR
- 6 February 2020
This work proposes a new model named LightGCN, including only the most essential component in GCN -- neighborhood aggregation -- for collaborative filtering, and is much easier to implement and train, exhibiting substantial improvements over Neural Graph Collaborative Filtering (NGCF) under exactly the same experimental setting.
High Efficiency Video Coding: High Efficiency Video Coding
Multiview Spectral Embedding
- Tian Xia, D. Tao, Tao Mei, Yongdong Zhang
- Computer ScienceIEEE Transactions on Systems, Man, and…
- 1 December 2010
A new spectral-embedding algorithm, namely, multiview spectral embedding (MSE), which can encode different features in different ways, to achieve a physically meaningful embedding and explores the complementary property of different views.
Deep Learning for Content-Based Image Retrieval: A Comprehensive Study
This paper investigates a framework of deep learning with application to CBIR tasks with an extensive set of empirical studies by examining a state-of-the-art deep learning method (Convolutional Neural Networks) for CBIr tasks under varied settings.
Multimodal Fusion with Recurrent Neural Networks for Rumor Detection on Microblogs
- Zhiwei Jin, Juan Cao, Han Guo, Yongdong Zhang, Jiebo Luo
- Computer ScienceACM Multimedia
- 19 October 2017
A novel Recurrent Neural Network with an attention mechanism (att-RNN) to fuse multimodal features for effective rumor detection and the results demonstrate the effectiveness of the proposed end-to-end att- RNN in detecting rumors with multi-modal contents.
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
A novel knowledge graph embedding model, Hierarchy-Aware Knowledge Graph Embedding (HAKE), which maps entities into the polar coordinate system and significantly outperforms existing state-of-the-art methods on benchmark datasets for the link prediction task.
CGNet: A Light-Weight Context Guided Network for Semantic Segmentation
- Tianyi Wu, Sheng Tang, Rui Zhang, Yongdong Zhang
- Computer ScienceIEEE Transactions on Image Processing
- 20 November 2018
This work proposes a novel Context Guided Network (CGNet), which is a light-weight and efficient network for semantic segmentation, and develops CGNet which captures contextual information in all stages of the network.
DR2-Net: Deep Residual Reconstruction Network for Image Compressive Sensing
WBSMDA: Within and Between Score for MiRNA-Disease Association prediction
The model of Within and Between Score for MiRNA-Disease Association prediction (WBSMDA) was developed to predict potential miRNAs associated with various complex diseases and would be a useful resource for potential miRNA-disease association identification.
APE-GAN: Adversarial Perturbation Elimination with GAN
- Guoqing Jin, Shiwei Shen, Dongming Zhang, Feng Dai, Yongdong Zhang
- Computer ScienceICASSP - IEEE International Conference on…
- 18 July 2017
An effective framework based Generative Adversarial Nets(GAN) is proposed to defense against the adversarial examples and the essense of the model is to eliminate the adversarian perturbations being highly aligned with the weight vectors of nueral models.