Search Results for author: Chen Gao

Found 47 papers, 27 papers with code

Robust Preference-Guided Denoising for Graph based Social Recommendation

no code implementations15 Mar 2023 Yuhan Quan, Jingtao Ding, Chen Gao, Lingling Yi, Depeng Jin, Yong Li

Graph Neural Network(GNN) based social recommendation models improve the prediction accuracy of user preference by leveraging GNN in exploiting preference similarity contained in social relations.


Dual-interest Factorization-heads Attention for Sequential Recommendation

no code implementations8 Feb 2023 GuanYu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang song, Zhiheng Li, Depeng Jin, Yong Li

In this paper, we propose Dual-interest Factorization-heads Attention for Sequential Recommendation (short for DFAR) consisting of feedback-aware encoding layer, dual-interest disentangling layer and prediction layer.

Disentanglement Sequential Recommendation

Robust Dynamic Radiance Fields

no code implementations5 Jan 2023 Yu-Lun Liu, Chen Gao, Andreas Meuleman, Hung-Yu Tseng, Ayush Saraf, Changil Kim, Yung-Yu Chuang, Johannes Kopf, Jia-Bin Huang

Dynamic radiance field reconstruction methods aim to model the time-varying structure and appearance of a dynamic scene.

Causal Inference in Recommender Systems: A Survey and Future Directions

1 code implementation26 Aug 2022 Chen Gao, Yu Zheng, Wenjie Wang, Fuli Feng, Xiangnan He, Yong Li

Afterward, we comprehensively review the existing work of causal inference-based recommendation, based on a taxonomy of what kind of problem causal inference addresses.

Causal Inference Click-Through Rate Prediction +2

DisenHCN: Disentangled Hypergraph Convolutional Networks for Spatiotemporal Activity Prediction

1 code implementation14 Aug 2022 Yinfeng Li, Chen Gao, Quanming Yao, Tong Li, Depeng Jin, Yong Li

In particular, we first unify the fine-grained user similarity and the complex matching between user preferences and spatiotemporal activity into a heterogeneous hypergraph.

Activity Prediction Graph Embedding +1

Practitioners Versus Users: A Value-Sensitive Evaluation of Current Industrial Recommender System Design

no code implementations8 Aug 2022 Zhilong Chen, Jinghua Piao, Xiaochong Lan, Hancheng Cao, Chen Gao, Zhicong Lu, Yong Li

Recommender systems are playing an increasingly important role in alleviating information overload and supporting users' various needs, e. g., consumption, socialization, and entertainment.

Fairness Recommendation Systems

Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation

no code implementations3 Aug 2022 Chang Meng, Ziqi Zhao, Wei Guo, Yingxue Zhang, Haolun Wu, Chen Gao, Dong Li, Xiu Li, Ruiming Tang

More specifically, we propose a novel Coarse-to-fine Knowledge-enhanced Multi-interest Learning (CKML) framework to learn shared and behavior-specific interests for different behaviors.

Target-Driven Structured Transformer Planner for Vision-Language Navigation

1 code implementation19 Jul 2022 Yusheng Zhao, Jinyu Chen, Chen Gao, Wenguan Wang, Lirong Yang, Haibing Ren, Huaxia Xia, Si Liu

Vision-language navigation is the task of directing an embodied agent to navigate in 3D scenes with natural language instructions.

Navigate Vision-Language Navigation

Cascading Residual Graph Convolutional Network for Multi-Behavior Recommendation

no code implementations26 May 2022 Mingshi Yan, Zhiyong Cheng, Chen Gao, Jing Sun, Fan Liu, Fuming Sun, Haojie Li

In particular, we design a cascading residual graph convolutional network structure, which enables our model to learn user preferences by continuously refining user embeddings across different types of behaviors.

Multi-Task Learning

Reinforced Structured State-Evolution for Vision-Language Navigation

1 code implementation CVPR 2022 Jinyu Chen, Chen Gao, Erli Meng, Qiong Zhang, Si Liu

However, the crucial navigation clues (i. e., object-level environment layout) for embodied navigation task is discarded since the maintained vector is essentially unstructured.

Navigate Vision and Language Navigation +1

3D-SPS: Single-Stage 3D Visual Grounding via Referred Point Progressive Selection

1 code implementation CVPR 2022 Junyu Luo, Jiahui Fu, Xianghao Kong, Chen Gao, Haibing Ren, Hao Shen, Huaxia Xia, Si Liu

3D visual grounding aims to locate the referred target object in 3D point cloud scenes according to a free-form language description.

Visual Grounding

Remaining Useful Life Prediction Using Temporal Deep Degradation Network for Complex Machinery with Attention-based Feature Extraction

no code implementations21 Feb 2022 Yuwen Qin, Ningbo Cai, Chen Gao, Yadong Zhang, Yonghong Cheng, Xin Chen

The degradation-related features extracted from the sensor streaming data with neural networks can dramatically improve the accuracy of the RUL prediction.

Progressive Feature Interaction Search for Deep Sparse Network

no code implementations NeurIPS 2021 Chen Gao, Yinfeng Li, Quanming Yao, Depeng Jin, Yong Li

Deep sparse networks (DSNs), of which the crux is exploring the high-order feature interactions, have become the state-of-the-art on the prediction task with high-sparsity features.

Neural Architecture Search

Session-aware Item-combination Recommendation with Transformer Network

1 code implementation13 Nov 2021 Tzu-Heng Lin, Chen Gao

In this paper, we detailedly describe our solution for the IEEE BigData Cup 2021: RL-based RecSys (Track 1: Item Combination Prediction).

Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks

1 code implementation5 Nov 2021 Zirui Zhu, Chen Gao, Xu Chen, Nian Li, Depeng Jin, Yong Li

With the hypergraph convolutional networks, the social relations can be modeled in a more fine-grained manner, which more accurately depicts real users' preferences, and benefits the recommendation performance.

Improving Location Recommendation with Urban Knowledge Graph

no code implementations1 Nov 2021 Chang Liu, Chen Gao, Depeng Jin, Yong Li

We first conduct information propagation on two sub-graphs to learn the representations of POIs and users.

DGCN: Diversified Recommendation with Graph Convolutional Networks

1 code implementation16 Aug 2021 Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, Yong Li

These years much effort has been devoted to improving the accuracy or relevance of the recommendation system.

Collaborative Filtering

Sequential Recommendation with Graph Neural Networks

1 code implementation27 Jun 2021 Jianxin Chang, Chen Gao, Yu Zheng, Yiqun Hui, Yanan Niu, Yang song, Depeng Jin, Yong Li

This helps explicitly distinguish users' core interests, by forming dense clusters in the interest graph.

Metric Learning Sequential Recommendation

Room-and-Object Aware Knowledge Reasoning for Remote Embodied Referring Expression

1 code implementation CVPR 2021 Chen Gao, Jinyu Chen, Si Liu, Luting Wang, Qiong Zhang, Qi Wu

The Remote Embodied Referring Expression (REVERIE) is a recently raised task that requires an agent to navigate to and localise a referred remote object according to a high-level language instruction.

Instruction Following Navigate +1

Efficient Data-specific Model Search for Collaborative Filtering

no code implementations14 Jun 2021 Chen Gao, Quanming Yao, Depeng Jin, Yong Li

In this way, we can combinatorially generalize data-specific CF models, which have not been visited in the literature, from SOTA ones.

AutoML Collaborative Filtering +1

PSGAN++: Robust Detail-Preserving Makeup Transfer and Removal

1 code implementation26 May 2021 Si Liu, Wentao Jiang, Chen Gao, Ran He, Jiashi Feng, Bo Li, Shuicheng Yan

In this paper, we address the makeup transfer and removal tasks simultaneously, which aim to transfer the makeup from a reference image to a source image and remove the makeup from the with-makeup image respectively.

Style Transfer

Dynamic View Synthesis from Dynamic Monocular Video

no code implementations ICCV 2021 Chen Gao, Ayush Saraf, Johannes Kopf, Jia-Bin Huang

We present an algorithm for generating novel views at arbitrary viewpoints and any input time step given a monocular video of a dynamic scene.

Learnable Embedding Sizes for Recommender Systems

1 code implementation ICLR 2021 Siyi Liu, Chen Gao, Yihong Chen, Depeng Jin, Yong Li

Existing works that try to address the problem always cause a significant drop in recommendation performance or suffers from the limitation of unaffordable training time cost.

Recommendation Systems Representation Learning

Language-Guided Global Image Editing via Cross-Modal Cyclic Mechanism

no code implementations ICCV 2021 Wentao Jiang, Ning Xu, Jiayun Wang, Chen Gao, Jing Shi, Zhe Lin, Si Liu

Given the cycle, we propose several free augmentation strategies to help our model understand various editing requests given the imbalanced dataset.

Portrait Neural Radiance Fields from a Single Image

no code implementations10 Dec 2020 Chen Gao, YiChang Shih, Wei-Sheng Lai, Chia-Kai Liang, Jia-Bin Huang

We present a method for estimating Neural Radiance Fields (NeRF) from a single headshot portrait.


Group-Buying Recommendation for Social E-Commerce

1 code implementation14 Oct 2020 Jun Zhang, Chen Gao, Depeng Jin, Yong Li

Group-buying recommendation for social e-commerce, which recommends an item list when users want to launch a group, plays an important role in the group success ratio and sales.

NAS-DIP: Learning Deep Image Prior with Neural Architecture Search

1 code implementation ECCV 2020 Yun-Chun Chen, Chen Gao, Esther Robb, Jia-Bin Huang

Recent work has shown that the structure of deep convolutional neural networks can be used as a structured image prior for solving various inverse image restoration tasks.

Image Restoration Image-to-Image Translation +2

Disentangling User Interest and Conformity for Recommendation with Causal Embedding

3 code implementations19 Jun 2020 Yu Zheng, Chen Gao, Xiang Li, Xiangnan He, Depeng Jin, Yong Li

We further demonstrate that the learned embeddings successfully capture the desired causes, and show that DICE guarantees the robustness and interpretability of recommendation.

Causal Inference

Recapture as You Want

no code implementations2 Jun 2020 Chen Gao, Si Liu, Ran He, Shuicheng Yan, Bo Li

LGR module utilizes body skeleton knowledge to construct a layout graph that connects all relevant part features, where graph reasoning mechanism is used to propagate information among part nodes to mine their relations.

Bundle Recommendation with Graph Convolutional Networks

1 code implementation7 May 2020 Jianxin Chang, Chen Gao, Xiangnan He, Yong Li, Depeng Jin

Existing solutions integrate user-item interaction modeling into bundle recommendation by sharing model parameters or learning in a multi-task manner, which cannot explicitly model the affiliation between items and bundles, and fail to explore the decision-making when a user chooses bundles.

Decision Making

Price-aware Recommendation with Graph Convolutional Networks

1 code implementation9 Mar 2020 Yu Zheng, Chen Gao, Xiangnan He, Yong Li, Depeng Jin

Price, an important factor in marketing --- which determines whether a user will make the final purchase decision on an item --- surprisingly, has received relatively little scrutiny.

Collaborative Filtering Marketing +1

Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition

1 code implementation NeurIPS 2019 Jinwoo Choi, Chen Gao, Joseph C. E. Messou, Jia-Bin Huang

We validate the effectiveness of our method by transferring our pre-trained model to three different tasks, including action classification, temporal localization, and spatio-temporal action detection.

Action Classification Action Detection +4

AdversarialNAS: Adversarial Neural Architecture Search for GANs

1 code implementation CVPR 2020 Chen Gao, Yunpeng Chen, Si Liu, Zhenxiong Tan, Shuicheng Yan

In this paper, we propose an AdversarialNAS method specially tailored for Generative Adversarial Networks (GANs) to search for a superior generative model on the task of unconditional image generation.

Image Generation Neural Architecture Search +1

PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer

1 code implementation CVPR 2020 Wentao Jiang, Si Liu, Chen Gao, Jie Cao, Ran He, Jiashi Feng, Shuicheng Yan

In this paper, we address the makeup transfer task, which aims to transfer the makeup from a reference image to a source image.

UGAN: Untraceable GAN for Multi-Domain Face Translation

no code implementations26 Jul 2019 Defa Zhu, Si Liu, Wentao Jiang, Chen Gao, Tianyi Wu, Qaingchang Wang, Guodong Guo

To address this issue, we propose a method called Untraceable GAN, which has a novel source classifier to differentiate which domain an image is translated from, and determines whether the translated image still retains the characteristics of the source domain.

Image-to-Image Translation Translation

LambdaOpt: Learn to Regularize Recommender Models in Finer Levels

1 code implementation28 May 2019 Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou, Yue Wang

We show how to employ LambdaOpt on matrix factorization, a classical model that is representative of a large family of recommender models.

Hyperparameter Optimization Recommendation Systems

Learning to Recommend with Multiple Cascading Behaviors

no code implementations21 Sep 2018 Chen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li, Tat-Seng Chua, Lina Yao, Yang song, Depeng Jin

To fully exploit the signal in the data of multiple types of behaviors, we perform a joint optimization based on the multi-task learning framework, where the optimization on a behavior is treated as a task.

Multi-Task Learning Recommendation Systems

iCAN: Instance-Centric Attention Network for Human-Object Interaction Detection

4 code implementations30 Aug 2018 Chen Gao, Yuliang Zou, Jia-Bin Huang

Our core idea is that the appearance of a person or an object instance contains informative cues on which relevant parts of an image to attend to for facilitating interaction prediction.

Human-Object Interaction Detection

Panoramic Robust PCA for Foreground-Background Separation on Noisy, Free-Motion Camera Video

no code implementations18 Dec 2017 Brian E. Moore, Chen Gao, Raj Rao Nadakuditi

We perform extensive numerical experiments on both static and moving camera video subject to a variety of dense and sparse corruptions.

Augmented Robust PCA For Foreground-Background Separation on Noisy, Moving Camera Video

no code implementations27 Sep 2017 Chen Gao, Brian E. Moore, Raj Rao Nadakuditi

This work presents a novel approach for robust PCA with total variation regularization for foreground-background separation and denoising on noisy, moving camera video.


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