Qiang Yang

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The Hong Kong University of Science and Technology

New Bright Professor of Engineering, Chair Professor and Head of Department of Computer Science and Engineering at Hong Kong University of Science and Technology

A Game-theoretic Approach Towards Collaborative Coded Computation Offloading

Coded distributed computing (CDC) has emerged as a promising approach be...
02/17/2021 ∙ by Jer Shyuan Ng, et al. ∙ 0 ∙ share

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Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack

Ever since Machine Learning as a Service (MLaaS) emerges as a viable bus...
02/08/2021 ∙ by Ding Sheng Ong, et al. ∙ 15 ∙ share

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TrNews: Heterogeneous User-Interest Transfer Learning for News Recommendation

We investigate how to solve the cross-corpus news recommendation for uns...
01/12/2021 ∙ by Guangneng Hu, et al. ∙ 0 ∙ share

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Privacy and Robustness in Federated Learning: Attacks and Defenses

As data are increasingly being stored in different silos and societies b...
12/07/2020 ∙ by Lingjuan Lyu, et al. ∙ 0 ∙ share

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Rethinking Uncertainty in Deep Learning: Whether and How it Improves Robustness

Deep neural networks (DNNs) are known to be prone to adversarial attacks...
11/27/2020 ∙ by Yilun Jin, et al. ∙ 0 ∙ share

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FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning

As an innovative solution for privacy-preserving machine learning (ML), ...
11/19/2020 ∙ by Di Chai, et al. ∙ 0 ∙ share

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PrivNet: Safeguarding Private Attributes in Transfer Learning for Recommendation

Transfer learning is an effective technique to improve a target recommen...
10/16/2020 ∙ by Guangneng Hu, et al. ∙ 0 ∙ share

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Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning

Transfer learning has become a common practice for training deep learnin...
08/25/2020 ∙ by Yinghua Zhang, et al. ∙ 21 ∙ share

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Protect, Show, Attend and Tell: Image Captioning Model with Ownership Protection

By and large, existing Intellectual Property Right (IPR) protection on d...
08/25/2020 ∙ by Jian Han Lim, et al. ∙ 2 ∙ share

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Privacy Threats Against Federated Matrix Factorization

Matrix Factorization has been very successful in practical recommendatio...
07/03/2020 ∙ by Dashan Gao, et al. ∙ 7 ∙ share

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Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks

This paper investigates capabilities of Privacy-Preserving Deep Learning...
06/20/2020 ∙ by Lixin Fan, et al. ∙ 19 ∙ share

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SenWave: Monitoring the Global Sentiments under the COVID-19 Pandemic

Since the first alert launched by the World Health Organization (5 Janua...
06/18/2020 ∙ by Qiang Yang, et al. ∙ 1 ∙ share

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Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning

In 5G and Beyond networks, Artificial Intelligence applications are expe...
05/31/2020 ∙ by Wei Yang Bryan Lim, et al. ∙ 0 ∙ share

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Graph Random Neural Network

Graph neural networks (GNNs) have generalized deep learning methods into...
05/22/2020 ∙ by Wenzheng Feng, et al. ∙ 57 ∙ share

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Network On Network for Tabular Data Classification in Real-world Applications

Tabular data is the most common data format adopted by our customers ran...
05/20/2020 ∙ by Yuanfei Luo, et al. ∙ 2 ∙ share

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Fisher Deep Domain Adaptation

Deep domain adaptation models learn a neural network in an unlabeled tar...
03/12/2020 ∙ by Yinghua Zhang, et al. ∙ 10 ∙ share

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Threats to Federated Learning: A Survey

With the emergence of data silos and popular privacy awareness, the trad...
03/04/2020 ∙ by Lingjuan Lyu, et al. ∙ 25 ∙ share

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A Survey towards Federated Semi-supervised Learning

The success of Artificial Intelligence (AI) should be largely attributed...
02/26/2020 ∙ by Yilun Jin, et al. ∙ 23 ∙ share

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Mechanism Design for Multi-Party Machine Learning

In a multi-party machine learning system, different parties cooperate on...
01/24/2020 ∙ by Mengjing Chen, et al. ∙ 0 ∙ share

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RPN: A Residual Pooling Network for Efficient Federated Learning

Federated learning is a new machine learning framework which enables dif...
01/23/2020 ∙ by Anbu Huang, et al. ∙ 14 ∙ share

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FedVision: An Online Visual Object Detection Platform Powered by Federated Learning

Visual object detection is a computer vision-based artificial intelligen...
01/17/2020 ∙ by Yang Liu, et al. ∙ 13 ∙ share

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A Communication Efficient Vertical Federated Learning Framework

One critical challenge for applying today's Artificial Intelligence (AI)...
12/24/2019 ∙ by Yang Liu, et al. ∙ 23 ∙ share

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Advances and Open Problems in Federated Learning

Federated learning (FL) is a machine learning setting where many clients...
12/10/2019 ∙ by Peter Kairouz, et al. ∙ 33 ∙ share

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A Quasi-Newton Method Based Vertical Federated Learning Framework for Logistic Regression

Data privacy and security becomes a major concern in building machine le...
12/01/2019 ∙ by Kai Yang, et al. ∙ 13 ∙ share

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Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning

Joint extraction of aspects and sentiments can be effectively formulated...
10/31/2019 ∙ by Zheng Li, et al. ∙ 0 ∙ share

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L2RS: A Learning-to-Rescore Mechanism for Automatic Speech Recognition

Modern Automatic Speech Recognition (ASR) systems primarily rely on scor...
10/25/2019 ∙ by Yuanfeng Song, et al. ∙ 0 ∙ share

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Federated Transfer Reinforcement Learning for Autonomous Driving

Reinforcement learning (RL) is widely used in autonomous driving tasks a...
10/14/2019 ∙ by Xinle Liang, et al. ∙ 16 ∙ share

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Federated Learning in Mobile Edge Networks: A Comprehensive Survey

In recent years, mobile devices are equipped with increasingly advanced ...
09/26/2019 ∙ by Wei Yang Bryan Lim, et al. ∙ 0 ∙ share

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Transfer Learning with Dynamic Distribution Adaptation

Transfer learning aims to learn robust classifiers for the target domain...
09/17/2019 ∙ by Jindong Wang, et al. ∙ 7 ∙ share

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HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography

Electroencephalography (EEG) classification techniques have been widely ...
09/11/2019 ∙ by Dashan Gao, et al. ∙ 0 ∙ share

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Secure Federated Matrix Factorization

To protect user privacy and meet law regulations, federated (machine) le...
06/12/2019 ∙ by Di Chai, et al. ∙ 0 ∙ share

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Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer Satisfaction

An effective content recommendation in modern social media platforms sho...
05/28/2019 ∙ by Wenyi Xiao, et al. ∙ 0 ∙ share

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Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting

Graph convolution network based approaches have been recently used to mo...
05/27/2019 ∙ by Xu Geng, et al. ∙ 2 ∙ share

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Easy Transfer Learning By Exploiting Intra-domain Structures

Transfer learning aims at transferring knowledge from a well-labeled dom...
04/02/2019 ∙ by Jindong Wang, et al. ∙ 18 ∙ share

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Learning to Transfer Examples for Partial Domain Adaptation

Domain adaptation is critical for learning in new and unseen environment...
03/28/2019 ∙ by Zhangjie Cao, et al. ∙ 12 ∙ share

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AutoML @ NeurIPS 2018 challenge: Design and Results

We organized a competition on Autonomous Lifelong Machine Learning with ...
03/12/2019 ∙ by Hugo Jair Escalante, et al. ∙ 12 ∙ share

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Federated Machine Learning: Concept and Applications

Today's AI still faces two major challenges. One is that in most industr...
02/13/2019 ∙ by Qiang Yang, et al. ∙ 14 ∙ share

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SecureBoost: A Lossless Federated Learning Framework

The protection of user privacy is an important concern in machine learni...
01/25/2019 ∙ by Kewei Cheng, et al. ∙ 6 ∙ share

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Federated Reinforcement Learning

In reinforcement learning, building policies of high-quality is challeng...
01/24/2019 ∙ by Hankz Hankui Zhuo, et al. ∙ 16 ∙ share

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Transfer Meets Hybrid: A Synthetic Approach for Cross-Domain Collaborative Filtering with Text

Collaborative filtering (CF) is the key technique for recommender system...
01/22/2019 ∙ by Guangneng Hu, et al. ∙ 6 ∙ share

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Secure Federated Transfer Learning

Machine learning relies on the availability of a vast amount of data for...
12/08/2018 ∙ by Yang Liu, et al. ∙ 0 ∙ share

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Building Ethics into Artificial Intelligence

As artificial intelligence (AI) systems become increasingly ubiquitous, ...
12/07/2018 ∙ by Han Yu, et al. ∙ 14 ∙ share

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Privacy-preserving Transfer Learning for Knowledge Sharing

In many practical machine-learning applications, it is critical to allow...
11/23/2018 ∙ by Xiawei Guo, et al. ∙ 8 ∙ share

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Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classification

Aspect-level sentiment classification (ASC) aims at identifying sentimen...
11/16/2018 ∙ by Zheng Li, et al. ∙ 0 ∙ share

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Smart City Development with Urban Transfer Learning

The rapid development of big data techniques has offered great opportuni...
08/05/2018 ∙ by Leye Wang, et al. ∙ 2 ∙ share

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Bike Flow Prediction with Multi-Graph Convolutional Networks

One fundamental issue in managing bike sharing systems is the bike flow ...
07/28/2018 ∙ by Di Chai, et al. ∙ 8 ∙ share

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Learning to Multitask

Multitask learning has shown promising performance in many applications ...
05/19/2018 ∙ by Yu Zhang, et al. ∙ 0 ∙ share

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Parameter Transfer Unit for Deep Neural Networks

Parameters in deep neural networks which are trained on large-scale data...
04/23/2018 ∙ by Yinghua Zhang, et al. ∙ 0 ∙ share

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Cross-domain Dialogue Policy Transfer via Simultaneous Speech-act and Slot Alignment

Dialogue policy transfer enables us to build dialogue policies in a targ...
04/20/2018 ∙ by Kaixiang Mo, et al. ∙ 0 ∙ share

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Millionaire: A Hint-guided Approach for Crowdsourcing

Modern machine learning is migrating to the era of complex models, which...
02/26/2018 ∙ by Bo Han, et al. ∙ 0 ∙ share

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Qiang Yang

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