Search Results for author: Hui Fang

Found 18 papers, 7 papers with code

Decentralized Matrix Factorization with Heterogeneous Differential Privacy

no code implementations1 Dec 2022 Wentao Hu, Hui Fang

Existing differentially private matrix factorization methods either assume the recommender is trusted, or can only provide a uniform level of privacy protection for all users and items with untrusted recommender.

Watermarking in Secure Federated Learning: A Verification Framework Based on Client-Side Backdooring

no code implementations14 Nov 2022 Wenyuan Yang, Shuo Shao, Yue Yang, Xiyao Liu, Ximeng Liu, Zhihua Xia, Gerald Schaefer, Hui Fang

In this paper, we propose a novel client-side FL watermarking scheme to tackle the copyright protection issue in secure FL with HE.

Federated Learning

Understanding Diversity in Session-Based Recommendation

1 code implementation29 Aug 2022 Qing Yin, Hui Fang, Zhu Sun, Yew-Soon Ong

Besides the "trade-off" relationship, they might be positively correlated with each other, that is, having a same-trend (win-win or lose-lose) relationship, which varies across different methods and datasets.

Session-Based Recommendations

DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation

2 code implementations22 Jun 2022 Zhu Sun, Hui Fang, Jie Yang, Xinghua Qu, Hongyang Liu, Di Yu, Yew-Soon Ong, Jie Zhang

Recently, one critical issue looms large in the field of recommender systems -- there are no effective benchmarks for rigorous evaluation -- which consequently leads to unreproducible evaluation and unfair comparison.

Benchmarking Recommendation Systems

Causality and Correlation Graph Modeling for Effective and Explainable Session-based Recommendation

no code implementations26 Jan 2022 Huizi Wu, Cong Geng, Hui Fang

Considering the varied interpretations and characteristics of causality and correlation relationship between items, in this study, we propose a novel method denoted as CGSR by jointly modeling causality and correlation relationship between items.

Session-Based Recommendations

MuSCLe: A Multi-Strategy Contrastive Learning Framework for Weakly Supervised Semantic Segmentation

no code implementations18 Jan 2022 Kunhao Yuan, Gerald Schaefer, Yu-Kun Lai, Yifan Wang, Xiyao Liu, Lin Guan, Hui Fang

Weakly supervised semantic segmentation (WSSS) has gained significant popularity since it relies only on weak labels such as image level annotations rather than pixel level annotations required by supervised semantic segmentation (SSS) methods.

Contrastive Learning Weakly supervised Semantic Segmentation +1

Image Disentanglement Autoencoder for Steganography Without Embedding

1 code implementation CVPR 2022 Xiyao Liu, Ziping Ma, Junxing Ma, Jian Zhang, Gerald Schaefer, Hui Fang

Conventional steganography approaches embed a secret message into a carrier for concealed communication but are prone to attack by recent advanced steganalysis tools.

Disentanglement Steganalysis

Analysis of an adaptive lead weighted ResNet for multiclass classification of 12-lead ECGs

no code implementations1 Dec 2021 Zhibin Zhao, Darcy Murphy, Hugh Gifford, Stefan Williams, Annie Darlington, Samuel D. Relton, Hui Fang, David C. Wong

Method: We proposed a squeeze and excite ResNet to automatically learn deep features from 12-lead ECGs, in order to identify 24 cardiac conditions.


Covidex: Neural Ranking Models and Keyword Search Infrastructure for the COVID-19 Open Research Dataset

1 code implementation EMNLP (sdp) 2020 Edwin Zhang, Nikhil Gupta, Raphael Tang, Xiao Han, Ronak Pradeep, Kuang Lu, Yue Zhang, Rodrigo Nogueira, Kyunghyun Cho, Hui Fang, Jimmy Lin

We present Covidex, a search engine that exploits the latest neural ranking models to provide information access to the COVID-19 Open Research Dataset curated by the Allen Institute for AI.

Joint Bilateral Learning for Real-time Universal Photorealistic Style Transfer

3 code implementations ECCV 2020 Xide Xia, Meng Zhang, Tianfan Xue, Zheng Sun, Hui Fang, Brian Kulis, Jiawen Chen

Photorealistic style transfer is the task of transferring the artistic style of an image onto a content target, producing a result that is plausibly taken with a camera.

Style Transfer

Research Commentary on Recommendations with Side Information: A Survey and Research Directions

no code implementations19 Sep 2019 Zhu Sun, Qing Guo, Jie Yang, Hui Fang, Guibing Guo, Jie Zhang, Robin Burke

This Research Commentary aims to provide a comprehensive and systematic survey of the recent research on recommender systems with side information.

Knowledge Graphs Recommendation Systems +1

Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations

1 code implementation30 Apr 2019 Hui Fang, Danning Zhang, Yiheng Shu, Guibing Guo

In the field of sequential recommendation, deep learning (DL)-based methods have received a lot of attention in the past few years and surpassed traditional models such as Markov chain-based and factorization-based ones.

Sequential Recommendation

Creatism: A deep-learning photographer capable of creating professional work

no code implementations11 Jul 2017 Hui Fang, Meng Zhang

In our system, we break down aesthetics into multiple aspects, each can be learned individually from a shared dataset of professional examples.

BIG-bench Machine Learning

Cannot find the paper you are looking for? You can Submit a new open access paper.