Search Results for author: Le Wu

Found 24 papers, 11 papers with code

A Review-aware Graph Contrastive Learning Framework for Recommendation

no code implementations26 Apr 2022 Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, Richang Hong, Meng Wang, Yong Li

Second, while most current models suffer from limited user behaviors, can we exploit the unique self-supervised signals in the review-aware graph to guide two recommendation components better?

Contrastive Learning Recommendation Systems +1

Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering

1 code implementation26 Apr 2022 Minghao Zhao, Le Wu, Yile Liang, Lei Chen, Jian Zhang, Qilin Deng, Kai Wang, Xudong Shen, Tangjie Lv, Runze Wu

While conventional CF models are known for facing the challenges of the popularity bias that favors popular items, one may wonder "Whether the existing graph-based CF models alleviate or exacerbate popularity bias of recommender systems?"

Collaborative Filtering Recommendation Systems

ProFairRec: Provider Fairness-aware News Recommendation

no code implementations10 Apr 2022 Tao Qi, Fangzhao Wu, Chuhan Wu, Peijie Sun, Le Wu, Xiting Wang, Yongfeng Huang, Xing Xie

To learn provider-fair representations from biased data, we employ provider-biased representations to inherit provider bias from data.

Fairness News Recommendation

LadRa-Net: Locally-Aware Dynamic Re-read Attention Net for Sentence Semantic Matching

no code implementations6 Aug 2021 Kun Zhang, Guangyi Lv, Le Wu, Enhong Chen, Qi Liu, Meng Wang

In order to overcome this problem and boost the performance of attention mechanism, we propose a novel dynamic re-read attention, which can pay close attention to one small region of sentences at each step and re-read the important parts for better sentence representations.

Language Modelling Natural Language Inference +1

Privileged Graph Distillation for Cold Start Recommendation

no code implementations31 May 2021 Shuai Wang, Kun Zhang, Le Wu, Haiping Ma, Richang Hong, Meng Wang

The teacher model is composed of a heterogeneous graph structure for warm users and items with privileged CF links.

Collaborative Filtering Recommendation Systems

Set2setRank: Collaborative Set to Set Ranking for Implicit Feedback based Recommendation

1 code implementation16 May 2021 Lei Chen, Le Wu, Kun Zhang, Richang Hong, Meng Wang

Despite the performance gain of these implicit feedback based models, the recommendation results are still far from satisfactory due to the sparsity of the observed item set for each user.

Collaborative Filtering

A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation

1 code implementation27 Apr 2021 Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang

Influenced by the great success of deep learning in computer vision and language understanding, research in recommendation has shifted to inventing new recommender models based on neural networks.

Collaborative Filtering Sequential Recommendation

Learning Fair Representations for Recommendation: A Graph-based Perspective

1 code implementation18 Feb 2021 Le Wu, Lei Chen, Pengyang Shao, Richang Hong, Xiting Wang, Meng Wang

For each user, this transformation is achieved under the adversarial learning of a user-centric graph, in order to obfuscate each sensitive feature between both the filtered user embedding and the sub graph structures of this user.

Fairness Recommendation Systems

R$^2$-Net: Relation of Relation Learning Network for Sentence Semantic Matching

no code implementations16 Dec 2020 Kun Zhang, Le Wu, Guangyi Lv, Meng Wang, Enhong Chen, Shulan Ruan

Sentence semantic matching is one of the fundamental tasks in natural language processing, which requires an agent to determine the semantic relation among input sentences.

Natural Language Processing Relation Classification

Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation

no code implementations24 May 2020 Le Wu, Yonghui Yang, Lei Chen, Defu Lian, Richang Hong, Meng Wang

The transfer network is designed to approximate the learned item embeddings from graph neural networks by taking each item's visual content as input, in order to tackle the new segment problem in the test phase.

Transfer Learning

Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach

2 code implementations28 Jan 2020 Lei Chen, Le Wu, Richang Hong, Kun Zhang, Meng Wang

Second, we propose a residual network structure that is specifically designed for CF with user-item interaction modeling, which alleviates the over smoothing problem in graph convolution aggregation operation with sparse user-item interaction data.

Collaborative Filtering Recommendation Systems +1

DiffNet++: A Neural Influence and Interest Diffusion Network for Social Recommendation

2 code implementations15 Jan 2020 Le Wu, Junwei Li, Peijie Sun, Richang Hong, Yong Ge, Meng Wang

Recently, we propose a preliminary work of a neural influence diffusion network (i. e., DiffNet) for social recommendation (Diffnet), which models the recursive social diffusion process to capture the higher-order relationships for each user.

Collaborative Filtering

Aesthetic Attributes Assessment of Images

2 code implementations11 Jul 2019 Xin Jin, Le Wu, Geng Zhao, Xiao-Dong Li, Xiaokun Zhang, Shiming Ge, Dongqing Zou, Bin Zhou, Xinghui Zhou

This is a new formula of image aesthetic assessment, which predicts aesthetic attributes captions together with the aesthetic score of each attribute.

Image Captioning Transfer Learning

Personalized Multimedia Item and Key Frame Recommendation

no code implementations1 Jun 2019 Le Wu, Lei Chen, Yonghui Yang, Richang Hong, Yong Ge, Xing Xie, Meng Wang

We argue that the key challenge of this problem lies in discovering users' visual profiles for key frame recommendation, as most recommendation models would fail without any users' fine-grained image behavior.

Explainable Fashion Recommendation: A Semantic Attribute Region Guided Approach

no code implementations30 May 2019 Min Hou, Le Wu, Enhong Chen, Zhi Li, Vincent W. Zheng, Qi Liu

When making cloth decisions, people usually show preferences for different semantic attributes (e. g., the clothes with v-neck collar).

Ranked #2 on Recommendation Systems on Amazon Fashion (using extra training data)

Recommendation Systems

A Neural Influence Diffusion Model for Social Recommendation

2 code implementations20 Apr 2019 Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang, Meng Wang

The key idea of our proposed model is that we design a layer-wise influence propagation structure to model how users' latent embeddings evolve as the social diffusion process continues.

Collaborative Filtering Recommendation Systems

Quality-aware Unpaired Image-to-Image Translation

no code implementations15 Mar 2019 Lei Chen, Le Wu, Zhenzhen Hu, Meng Wang

To tackle the above two challenges, in this paper, we propose a unified quality-aware GAN-based framework for unpaired image-to-image translation, where a quality-aware loss is explicitly incorporated by comparing each source image and the reconstructed image at the domain level.

Image Quality Assessment Image-to-Image Translation +1

SocialGCN: An Efficient Graph Convolutional Network based Model for Social Recommendation

no code implementations7 Nov 2018 Le Wu, Peijie Sun, Richang Hong, Yanjie Fu, Xiting Wang, Meng Wang

Based on a classical CF model, the key idea of our proposed model is that we borrow the strengths of GCNs to capture how users' preferences are influenced by the social diffusion process in social networks.

Collaborative Filtering Recommendation Systems

A Hierarchical Attention Model for Social Contextual Image Recommendation

1 code implementation3 Jun 2018 Le Wu, Lei Chen, Richang Hong, Yanjie Fu, Xing Xie, Meng Wang

After that, we design a hierarchical attention network that naturally mirrors the hierarchical relationship (elements in each aspects level, and the aspect level) of users' latent interests with the identified key aspects.

Multi-level Chaotic Maps for 3D Textured Model Encryption

no code implementations25 Sep 2017 Xin Jin, Shuyun Zhu, Le Wu, Geng Zhao, Xiao-Dong Li, Quan Zhou, Huimin Lu

In this work, a multi-level chaotic maps models for 3D textured encryption was presented by observing the different contributions for recognizing cipher 3D models between vertices (point cloud), polygons and textures.

Predicting Aesthetic Score Distribution through Cumulative Jensen-Shannon Divergence

2 code implementations23 Aug 2017 Xin Jin, Le Wu, Xiao-Dong Li, Siyu Chen, Siwei Peng, Jingying Chi, Shiming Ge, Chenggen Song, Geng Zhao

Thus, a novel CNN based on the Cumulative distribution with Jensen-Shannon divergence (CJS-CNN) is presented to predict the aesthetic score distribution of human ratings, with a new reliability-sensitive learning method based on the kurtosis of the score distribution, which eliminates the requirement of the original full data of human ratings (without normalization).

ILGNet: Inception Modules with Connected Local and Global Features for Efficient Image Aesthetic Quality Classification using Domain Adaptation

2 code implementations7 Oct 2016 Xin Jin, Le Wu, Xiao-Dong Li, Xiaokun Zhang, Jingying Chi, Siwei Peng, Shiming Ge, Geng Zhao, Shuying Li

Thus, it is easy to use a pre-trained GoogLeNet for large-scale image classification problem and fine tune our connected layers on an large scale database of aesthetic related images: AVA, i. e. \emph{domain adaptation}.

Domain Adaptation General Classification +2

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