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LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
TLDR
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. Expand
Multiview Spectral Embedding
TLDR
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. Expand
Deep Learning for Content-Based Image Retrieval: A Comprehensive Study
TLDR
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. Expand
DR2-Net: Deep Residual Reconstruction Network for Image Compressive Sensing
TLDR
A novel Deep Residual Reconstruction Network (DR2-Net) to reconstruct the image from its Compressively Sensed measurement by outperforms traditional iterative methods and recent deep learning-based methods by large margins at measurement rates 0.01, 0.1, and 0.25. Expand
CGNet: A Light-Weight Context Guided Network for Semantic Segmentation
TLDR
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. Expand
News Verification by Exploiting Conflicting Social Viewpoints in Microblogs
TLDR
This paper discovers conflicting viewpoints in news tweets with a topic model method, and builds a credibility propagation network of tweets linked with supporting or opposing relations that generates the final evaluation result for news. Expand
Multimodal Fusion with Recurrent Neural Networks for Rumor Detection on Microblogs
TLDR
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. Expand
APE-GAN: Adversarial Perturbation Elimination with GAN
TLDR
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. Expand
Deep Representation Learning With Part Loss for Person Re-Identification
TLDR
Experimental results on three person ReID datasets, i.e., Market1501, CUHK03, and VIPeR, show that the proposed deep representation learning procedure named part loss network outperforms existing deep representations. Expand
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