Search Results for author: Jiawei Chen

Found 73 papers, 38 papers with code

Revisiting the Message Passing in Heterophilous Graph Neural Networks

no code implementations28 May 2024 Zhuonan Zheng, Yuanchen Bei, Sheng Zhou, Yao Ma, Ming Gu, Hongjia Xu, Chengyu Lai, Jiawei Chen, Jiajun Bu

Based on HTMP and empirical analysis, we reveal that the success of message passing in existing HTGNNs is attributed to implicitly enhancing the compatibility matrix among classes.

Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Model

no code implementations1 May 2024 Yu Cui, Feng Liu, Pengbo Wang, Bohao Wang, Heng Tang, Yi Wan, Jun Wang, Jiawei Chen

Owing to their powerful semantic reasoning capabilities, Large Language Models (LLMs) have been effectively utilized as recommenders, achieving impressive performance.

Knowledge Distillation Language Modelling +1

Efficiency in Focus: LayerNorm as a Catalyst for Fine-tuning Medical Visual Language Pre-trained Models

no code implementations25 Apr 2024 Jiawei Chen, Dingkang Yang, Yue Jiang, Mingcheng Li, Jinjie Wei, Xiaolu Hou, Lihua Zhang

In the realm of Medical Visual Language Models (Med-VLMs), the quest for universal efficient fine-tuning mechanisms remains paramount, especially given researchers in interdisciplinary fields are often extremely short of training resources, yet largely unexplored.

Medical Visual Question Answering Question Answering +1

How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective

no code implementations18 Apr 2024 Siyi Lin, Chongming Gao, Jiawei Chen, Sheng Zhou, Binbin Hu, Chun Chen, Can Wang

Building on these insights, we propose a novel debiasing strategy that leverages a spectral norm regularizer to penalize the magnitude of the principal singular value.

Fairness Recommendation Systems

SIGformer: Sign-aware Graph Transformer for Recommendation

1 code implementation18 Apr 2024 Sirui Chen, Jiawei Chen, Sheng Zhou, Bohao Wang, Shen Han, Chanfei Su, Yuqing Yuan, Can Wang

Integrating both positive and negative feedback to form a signed graph can lead to a more comprehensive understanding of user preferences.

Recommendation Systems

FaceCat: Enhancing Face Recognition Security with a Unified Generative Model Framework

no code implementations14 Apr 2024 Jiawei Chen, Xiao Yang, Yinpeng Dong, Hang Su, Jianteng Peng, Zhaoxia Yin

Motivated by the rich structural and detailed features of face generative models, we propose FaceCat which utilizes the face generative model as a pre-trained model to improve the performance of FAS and FAD.

Face Anti-Spoofing Face Recognition +1

Few-shot Named Entity Recognition via Superposition Concept Discrimination

1 code implementation25 Mar 2024 Jiawei Chen, Hongyu Lin, Xianpei Han, Yaojie Lu, Shanshan Jiang, Bin Dong, Le Sun

Then a superposition instance retriever is applied to retrieve corresponding instances of these superposition concepts from large-scale text corpus.

Active Learning few-shot-ner +4

Can LLMs' Tuning Methods Work in Medical Multimodal Domain?

no code implementations11 Mar 2024 Jiawei Chen, Yue Jiang, Dingkang Yang, Mingcheng Li, Jinjie Wei, Ziyun Qian, Lihua Zhang

We show the different impacts of fine-tuning methods for large models on medical VLMs and develop the most efficient ways to fine-tune medical VLP models.

Transfer Learning World Knowledge

Self-Retrieval: Building an Information Retrieval System with One Large Language Model

no code implementations23 Feb 2024 Qiaoyu Tang, Jiawei Chen, Bowen Yu, Yaojie Lu, Cheng Fu, Haiyang Yu, Hongyu Lin, Fei Huang, Ben He, Xianpei Han, Le Sun, Yongbin Li

The rise of large language models (LLMs) has transformed the role of information retrieval (IR) systems in the way to humans accessing information.

Information Retrieval Language Modelling +2

Distributionally Robust Graph-based Recommendation System

1 code implementation20 Feb 2024 Bohao Wang, Jiawei Chen, Changdong Li, Sheng Zhou, Qihao Shi, Yang Gao, Yan Feng, Chun Chen, Can Wang

DR-GNN addresses two core challenges: 1) To enable DRO to cater to graph data intertwined with GNN, we reinterpret GNN as a graph smoothing regularizer, thereby facilitating the nuanced application of DRO; 2) Given the typically sparse nature of recommendation data, which might impede robust optimization, we introduce slight perturbations in the training distribution to expand its support.

Recommendation Systems

Knowledge Translation: A New Pathway for Model Compression

1 code implementation11 Jan 2024 Wujie Sun, Defang Chen, Jiawei Chen, Yan Feng, Chun Chen, Can Wang

Deep learning has witnessed significant advancements in recent years at the cost of increasing training, inference, and model storage overhead.

Data Augmentation Model Compression +1

MISS: A Generative Pretraining and Finetuning Approach for Med-VQA

no code implementations10 Jan 2024 Jiawei Chen, Dingkang Yang, Yue Jiang, Yuxuan Lei, Lihua Zhang

However, most methods in the medical field treat VQA as an answer classification task which is difficult to transfer to practical application scenarios.

Medical Visual Question Answering Multi-Task Learning +3

BSL: Understanding and Improving Softmax Loss for Recommendation

1 code implementation20 Dec 2023 Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Jizhi Zhang, Xiang Wang

Loss functions steer the optimization direction of recommendation models and are critical to model performance, but have received relatively little attention in recent recommendation research.

Fairness

How Robust is Google's Bard to Adversarial Image Attacks?

1 code implementation21 Sep 2023 Yinpeng Dong, Huanran Chen, Jiawei Chen, Zhengwei Fang, Xiao Yang, Yichi Zhang, Yu Tian, Hang Su, Jun Zhu

By attacking white-box surrogate vision encoders or MLLMs, the generated adversarial examples can mislead Bard to output wrong image descriptions with a 22% success rate based solely on the transferability.

Adversarial Robustness Chatbot +1

Benchmarking Large Language Models in Retrieval-Augmented Generation

1 code implementation4 Sep 2023 Jiawei Chen, Hongyu Lin, Xianpei Han, Le Sun

In this paper, we systematically investigate the impact of Retrieval-Augmented Generation on large language models.

Benchmarking counterfactual +2

CDR: Conservative Doubly Robust Learning for Debiased Recommendation

1 code implementation13 Aug 2023 Zijie Song, Jiawei Chen, Sheng Zhou, Qihao Shi, Yan Feng, Chun Chen, Can Wang

In recommendation systems (RS), user behavior data is observational rather than experimental, resulting in widespread bias in the data.

Imputation Recommendation Systems

Homophily-enhanced Structure Learning for Graph Clustering

1 code implementation10 Aug 2023 Ming Gu, Gaoming Yang, Sheng Zhou, Ning Ma, Jiawei Chen, Qiaoyu Tan, Meihan Liu, Jiajun Bu

Graph clustering is a fundamental task in graph analysis, and recent advances in utilizing graph neural networks (GNNs) have shown impressive results.

Clustering Graph Clustering +1

AdvFAS: A robust face anti-spoofing framework against adversarial examples

1 code implementation4 Aug 2023 Jiawei Chen, Xiao Yang, Heng Yin, Mingzhi Ma, Bihui Chen, Jianteng Peng, Yandong Guo, Zhaoxia Yin, Hang Su

Ensuring the reliability of face recognition systems against presentation attacks necessitates the deployment of face anti-spoofing techniques.

Adversarial Defense Face Anti-Spoofing +1

OpenGSL: A Comprehensive Benchmark for Graph Structure Learning

1 code implementation NeurIPS 2023 Zhiyao Zhou, Sheng Zhou, Bochao Mao, Xuanyi Zhou, Jiawei Chen, Qiaoyu Tan, Daochen Zha, Yan Feng, Chun Chen, Can Wang

Moreover, we observe that the learned graph structure demonstrates a strong generalization ability across different GNN models, despite the high computational and space consumption.

Graph structure learning Representation Learning

How Graph Convolutions Amplify Popularity Bias for Recommendation?

1 code implementation24 May 2023 Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He

Through theoretical analyses, we identify two fundamental factors: (1) with graph convolution (\textit{i. e.,} neighborhood aggregation), popular items exert larger influence than tail items on neighbor users, making the users move towards popular items in the representation space; (2) after multiple times of graph convolution, popular items would affect more high-order neighbors and become more influential.

Recommendation Systems

Learning In-context Learning for Named Entity Recognition

2 code implementations18 May 2023 Jiawei Chen, Yaojie Lu, Hongyu Lin, Jie Lou, Wei Jia, Dai Dai, Hua Wu, Boxi Cao, Xianpei Han, Le Sun

M}$, and a new entity extractor can be implicitly constructed by applying new instruction and demonstrations to PLMs, i. e., $\mathcal{ (\lambda .

few-shot-ner Few-shot NER +4

Retentive or Forgetful? Diving into the Knowledge Memorizing Mechanism of Language Models

no code implementations16 May 2023 Boxi Cao, Qiaoyu Tang, Hongyu Lin, Shanshan Jiang, Bin Dong, Xianpei Han, Jiawei Chen, Tianshu Wang, Le Sun

Memory is one of the most essential cognitive functions serving as a repository of world knowledge and episodes of activities.

World Knowledge

Life Regression based Patch Slimming for Vision Transformers

no code implementations11 Apr 2023 Jiawei Chen, Lin Chen, Jiang Yang, Tianqi Shi, Lechao Cheng, Zunlei Feng, Mingli Song

In this study, we tackle the patch slimming problem from a different perspective by proposing a life regression module that determines the lifespan of each image patch in one go.

regression

Adap-$τ$: Adaptively Modulating Embedding Magnitude for Recommendation

2 code implementations9 Feb 2023 Jiawei Chen, Junkang Wu, Jiancan Wu, Sheng Zhou, Xuezhi Cao, Xiangnan He

Recent years have witnessed the great successes of embedding-based methods in recommender systems.

Recommendation Systems

FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion

no code implementations7 Feb 2023 Wentao Shi, Junkang Wu, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Wei Wu, Xiangnan He

Specifically, they suffer from two main limitations: 1) existing Graph Convolutional Network (GCN) methods in hyperbolic space rely on tangent space approximation, which would incur approximation error in representation learning, and 2) due to the lack of inner product operation definition in hyperbolic space, existing methods can only measure the plausibility of facts (links) with hyperbolic distance, which is difficult to capture complex data patterns.

Knowledge Graph Completion Representation Learning

On the Theories Behind Hard Negative Sampling for Recommendation

1 code implementation7 Feb 2023 Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao, Xiangnan He

Secondly, we prove that OPAUC has a stronger connection with Top-K evaluation metrics than AUC and verify it with simulation experiments.

Recommendation Systems

ResGrad: Residual Denoising Diffusion Probabilistic Models for Text to Speech

1 code implementation30 Dec 2022 Zehua Chen, Yihan Wu, Yichong Leng, Jiawei Chen, Haohe Liu, Xu Tan, Yang Cui, Ke Wang, Lei He, Sheng Zhao, Jiang Bian, Danilo Mandic

Denoising Diffusion Probabilistic Models (DDPMs) are emerging in text-to-speech (TTS) synthesis because of their strong capability of generating high-fidelity samples.

Denoising

Robust Sequence Networked Submodular Maximization

no code implementations28 Dec 2022 Qihao Shi, Bingyang Fu, Can Wang, Jiawei Chen, Sheng Zhou, Yan Feng, Chun Chen

The approximation ratio of the algorithm depends both on the number of the removed elements and the network topology.

Link Prediction

Unbiased Knowledge Distillation for Recommendation

1 code implementation27 Nov 2022 Gang Chen, Jiawei Chen, Fuli Feng, Sheng Zhou, Xiangnan He

Traditional solutions first train a full teacher model from the training data, and then transfer its knowledge (\ie \textit{soft labels}) to supervise the learning of a compact student model.

Knowledge Distillation Model Compression +1

A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions

1 code implementation15 Jun 2022 Sheng Zhou, Hongjia Xu, Zhuonan Zheng, Jiawei Chen, Zhao Li, Jiajun Bu, Jia Wu, Xin Wang, Wenwu Zhu, Martin Ester

Motivated by the tremendous success of deep learning in clustering, one of the most fundamental machine learning tasks, and the large number of recent advances in this direction, in this paper we conduct a comprehensive survey on deep clustering by proposing a new taxonomy of different state-of-the-art approaches.

Clustering Deep Clustering +1

Confidence-aware Self-Semantic Distillation on Knowledge Graph Embedding

no code implementations7 Jun 2022 Yichen Liu, Jiawei Chen, Defang Chen, Zhehui Zhou, Yan Feng, Can Wang

Knowledge Graph Embedding (KGE), which projects entities and relations into continuous vector spaces, have garnered significant attention.

Knowledge Distillation Knowledge Graph Embedding +2

BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis

1 code implementation30 May 2022 Yichong Leng, Zehua Chen, Junliang Guo, Haohe Liu, Jiawei Chen, Xu Tan, Danilo Mandic, Lei He, Xiang-Yang Li, Tao Qin, Sheng Zhao, Tie-Yan Liu

Combining this novel perspective of two-stage synthesis with advanced generative models (i. e., the diffusion models), the proposed BinauralGrad is able to generate accurate and high-fidelity binaural audio samples.

Audio Synthesis

NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality

3 code implementations9 May 2022 Xu Tan, Jiawei Chen, Haohe Liu, Jian Cong, Chen Zhang, Yanqing Liu, Xi Wang, Yichong Leng, YuanHao Yi, Lei He, Frank Soong, Tao Qin, Sheng Zhao, Tie-Yan Liu

In this paper, we answer these questions by first defining the human-level quality based on the statistical significance of subjective measure and introducing appropriate guidelines to judge it, and then developing a TTS system called NaturalSpeech that achieves human-level quality on a benchmark dataset.

 Ranked #1 on Text-To-Speech Synthesis on LJSpeech (using extra training data)

Sentence Speech Synthesis +1

Time-Series Domain Adaptation via Sparse Associative Structure Alignment: Learning Invariance and Variance

no code implementations7 May 2022 Zijian Li, Ruichu Cai, Jiawei Chen, Yuguan Yan, Wei Chen, Keli Zhang, Junjian Ye

Based on this inspiration, we investigate the domain-invariant unweighted sparse associative structures and the domain-variant strengths of the structures.

Time Series Time Series Analysis +2

CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System

1 code implementation4 Apr 2022 Chongming Gao, Shiqi Wang, Shijun Li, Jiawei Chen, Xiangnan He, Wenqiang Lei, Biao Li, Yuan Zhang, Peng Jiang

The basic idea is to first learn a causal user model on historical data to capture the overexposure effect of items on user satisfaction.

Causal Inference counterfactual +2

Few-shot Named Entity Recognition with Self-describing Networks

1 code implementation ACL 2022 Jiawei Chen, Qing Liu, Hongyu Lin, Xianpei Han, Le Sun

In this paper, we propose a self-describing mechanism for few-shot NER, which can effectively leverage illustrative instances and precisely transfer knowledge from external resources by describing both entity types and mentions using a universal concept set.

Few-shot NER Named Entity Recognition

KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems

3 code implementations22 Feb 2022 Chongming Gao, Shijun Li, Wenqiang Lei, Jiawei Chen, Biao Li, Peng Jiang, Xiangnan He, Jiaxin Mao, Tat-Seng Chua

The progress of recommender systems is hampered mainly by evaluation as it requires real-time interactions between humans and systems, which is too laborious and expensive.

Recommendation Systems User Simulation

IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search

1 code implementation10 Feb 2022 Dian Cheng, Jiawei Chen, Wenjun Peng, Wenqin Ye, Fuyu Lv, Tao Zhuang, Xiaoyi Zeng, Xiangnan He

On this basis, we develop a specific interactive hypergraph neural network to explicitly encode the structure information (i. e., collaborative signal) into the embedding process.

Representation Learning

Neighboring Backdoor Attacks on Graph Convolutional Network

no code implementations17 Jan 2022 Liang Chen, Qibiao Peng, Jintang Li, Yang Liu, Jiawei Chen, Yong Li, Zibin Zheng

To address such a challenge, we set the trigger as a single node, and the backdoor is activated when the trigger node is connected to the target node.

Backdoor Attack

Speech-T: Transducer for Text to Speech and Beyond

no code implementations NeurIPS 2021 Jiawei Chen, Xu Tan, Yichong Leng, Jin Xu, Guihua Wen, Tao Qin, Tie-Yan Liu

Experiments on LJSpeech datasets demonstrate that Speech-T 1) is more robust than the attention based autoregressive TTS model due to its inherent monotonic alignments between text and speech; 2) naturally supports streaming TTS with good voice quality; and 3) enjoys the benefit of joint modeling TTS and ASR in a single network.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Popularity Bias Is Not Always Evil: Disentangling Benign and Harmful Bias for Recommendation

no code implementations16 Sep 2021 Zihao Zhao, Jiawei Chen, Sheng Zhou, Xiangnan He, Xuezhi Cao, Fuzheng Zhang, Wei Wu

To sufficiently exploit such important information for recommendation, it is essential to disentangle the benign popularity bias caused by item quality from the harmful popularity bias caused by conformity.

Recommendation Systems

Honey or Poison? Solving the Trigger Curse in Few-shot Event Detection via Causal Intervention

1 code implementation EMNLP 2021 Jiawei Chen, Hongyu Lin, Xianpei Han, Le Sun

In this paper, we identify and solve the trigger curse problem in few-shot event detection (FSED) from a causal view.

Event Detection

InDuDoNet: An Interpretable Dual Domain Network for CT Metal Artifact Reduction

1 code implementation11 Sep 2021 Hong Wang, Yuexiang Li, Haimiao Zhang, Jiawei Chen, Kai Ma, Deyu Meng, Yefeng Zheng

For the task of metal artifact reduction (MAR), although deep learning (DL)-based methods have achieved promising performances, most of them suffer from two problems: 1) the CT imaging geometry constraint is not fully embedded into the network during training, leaving room for further performance improvement; 2) the model interpretability is lack of sufficient consideration.

Metal Artifact Reduction

DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network

2 code implementations22 Aug 2021 Junkang Wu, Wentao Shi, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Fuzheng Zhang, Wei Wu, Xiangnan He

Knowledge graph completion (KGC) has become a focus of attention across deep learning community owing to its excellent contribution to numerous downstream tasks.

Disentanglement Graph Attention +1

MM-ViT: Multi-Modal Video Transformer for Compressed Video Action Recognition

no code implementations20 Aug 2021 Jiawei Chen, Chiu Man Ho

This paper presents a pure transformer-based approach, dubbed the Multi-Modal Video Transformer (MM-ViT), for video action recognition.

Action Recognition Optical Flow Estimation +1

Distilling Holistic Knowledge with Graph Neural Networks

1 code implementation ICCV 2021 Sheng Zhou, Yucheng Wang, Defang Chen, Jiawei Chen, Xin Wang, Can Wang, Jiajun Bu

The holistic knowledge is represented as a unified graph-based embedding by aggregating individual knowledge from relational neighborhood samples with graph neural networks, the student network is learned by distilling the holistic knowledge in a contrastive manner.

Knowledge Distillation

Time-aware Path Reasoning on Knowledge Graph for Recommendation

1 code implementation5 Aug 2021 Yuyue Zhao, Xiang Wang, Jiawei Chen, Yashen Wang, Wei Tang, Xiangnan He, Haiyong Xie

In this work, we propose a novel Time-aware Path reasoning for Recommendation (TPRec for short) method, which leverages the potential of temporal information to offer better recommendation with plausible explanations.

Explainable Recommendation Relation Extraction

Single-shot structured illumination microscopy

no code implementations13 Jul 2021 Qinnan Zhang, En Bo, Jiawei Chen, Jiaosheng Li, Heming Jiang, Xiaoxu Lu, Liyun Zhong, Jindong Tian

In this paper, we report a novel technique termed single-shot SIM, to overcome these limitations.

Super-Resolution

Mutual-GAN: Towards Unsupervised Cross-Weather Adaptation with Mutual Information Constraint

no code implementations30 Jun 2021 Jiawei Chen, Yuexiang Li, Kai Ma, Yefeng Zheng

In practical applications, the outdoor weather and illumination are changeable, e. g., cloudy and nighttime, which results in a significant drop of semantic segmentation accuracy of CNN only trained with daytime data.

Autonomous Driving Generative Adversarial Network +4

CausCF: Causal Collaborative Filtering for RecommendationEffect Estimation

no code implementations28 May 2021 Xu Xie, Zhaoyang Liu, Shiwen Wu, Fei Sun, Cihang Liu, Jiawei Chen, Jinyang Gao, Bin Cui, Bolin Ding

It is based on the idea that similar users not only have a similar taste on items, but also have similar treatment effect under recommendations.

Collaborative Filtering Recommendation Systems

AutoDebias: Learning to Debias for Recommendation

1 code implementation10 May 2021 Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, Keping Yang

This provides a valuable opportunity to develop a universal solution for debiasing, e. g., by learning the debiasing parameters from data.

Imputation Meta-Learning +1

A General Framework for Learning Prosodic-Enhanced Representation of Rap Lyrics

no code implementations23 Mar 2021 Hongru Liang, Haozheng Wang, Qian Li, Jun Wang, Guandong Xu, Jiawei Chen, Jin-Mao Wei, Zhenglu Yang

Learning and analyzing rap lyrics is a significant basis for many web applications, such as music recommendation, automatic music categorization, and music information retrieval, due to the abundant source of digital music in the World Wide Web.

Information Retrieval Music Information Retrieval +3

Time Series Domain Adaptation via Sparse Associative Structure Alignment

no code implementations22 Dec 2020 Ruichu Cai, Jiawei Chen, Zijian Li, Wei Chen, Keli Zhang, Junjian Ye, Zhuozhang Li, Xiaoyan Yang, Zhenjie Zhang

To reduce the difficulty in the discovery of causal structure, we relax it to the sparse associative structure and propose a novel sparse associative structure alignment model for domain adaptation.

Domain Adaptation Time Series +1

CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation

no code implementations16 Nov 2020 Jiawei Chen, Chengquan Jiang, Can Wang, Sheng Zhou, Yan Feng, Chun Chen, Martin Ester, Xiangnan He

To deal with these problems, we propose an efficient and effective collaborative sampling method CoSam, which consists of: (1) a collaborative sampler model that explicitly leverages user-item interaction information in sampling probability and exhibits good properties of normalization, adaption, interaction information awareness, and sampling efficiency; and (2) an integrated sampler-recommender framework, leveraging the sampler model in prediction to offset the bias caused by uneven sampling.

Recommendation Systems

SamWalker++: recommendation with informative sampling strategy

1 code implementation16 Nov 2020 Can Wang, Jiawei Chen, Sheng Zhou, Qihao Shi, Yan Feng, Chun Chen

However, the social network information may not be available in many recommender systems, which hinders application of SamWalker.

Recommendation Systems

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System

1 code implementation29 Oct 2020 Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, JinFeng Yi, Xiangnan He

Existing work addresses this issue with Inverse Propensity Weighting (IPW), which decreases the impact of popular items on the training and increases the impact of long-tail items.

counterfactual Counterfactual Inference +3

On the Equivalence of Decoupled Graph Convolution Network and Label Propagation

1 code implementation23 Oct 2020 Hande Dong, Jiawei Chen, Fuli Feng, Xiangnan He, Shuxian Bi, Zhaolin Ding, Peng Cui

The original design of Graph Convolution Network (GCN) couples feature transformation and neighborhood aggregation for node representation learning.

Node Classification Pseudo Label +1

HiFiSinger: Towards High-Fidelity Neural Singing Voice Synthesis

1 code implementation3 Sep 2020 Jiawei Chen, Xu Tan, Jian Luan, Tao Qin, Tie-Yan Liu

To tackle the difficulty of singing modeling caused by high sampling rate (wider frequency band and longer waveform), we introduce multi-scale adversarial training in both the acoustic model and vocoder to improve singing modeling.

Singing Voice Synthesis Vocal Bursts Intensity Prediction

Residual Frames with Efficient Pseudo-3D CNN for Human Action Recognition

no code implementations3 Aug 2020 Jiawei Chen, Jenson Hsiao, Chiu Man Ho

Empirical results confirm the efficiency and effectiveness of residual frames as well as the proposed pseudo-3D convolution module.

Action Recognition Optical Flow Estimation +2

Generative Adversarial Networks for Video-to-Video Domain Adaptation

no code implementations17 Apr 2020 Jiawei Chen, Yuexiang Li, Kai Ma, Yefeng Zheng

Two colonoscopic datasets from different centres, i. e., CVC-Clinic and ETIS-Larib, are adopted to evaluate the performance of domain adaptation of our VideoGAN.

Domain Adaptation Generative Adversarial Network +1

Fast Adaptively Weighted Matrix Factorization for Recommendation with Implicit Feedback

no code implementations4 Mar 2020 Jiawei Chen, Can Wang, Sheng Zhou, Qihao Shi, Jingbang Chen, Yan Feng, Chun Chen

A popular and effective approach for implicit recommendation is to treat unobserved data as negative but downweight their confidence.

A Cyclically-Trained Adversarial Network for Invariant Representation Learning

no code implementations21 Jun 2019 Jiawei Chen, Janusz Konrad, Prakash Ishwar

Specifically, we propose a cyclically-trained adversarial network to learn a mapping from image space to latent representation space and back such that the latent representation is invariant to a specified factor of variation (e. g., identity).

Representation Learning

Semi-Coupled Two-Stream Fusion ConvNets for Action Recognition at Extremely Low Resolutions

no code implementations12 Oct 2016 Jiawei Chen, Jonathan Wu, Janusz Konrad, Prakash Ishwar

Deep convolutional neural networks (ConvNets) have been recently shown to attain state-of-the-art performance for action recognition on standard-resolution videos.

Action Recognition Temporal Action Localization

Building A Large Concept Bank for Representing Events in Video

no code implementations29 Mar 2014 Yin Cui, Dong Liu, Jiawei Chen, Shih-Fu Chang

In this paper, we propose to build Concept Bank, the largest concept library consisting of 4, 876 concepts specifically designed to cover 631 real-world events.

Event Detection Retrieval

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