Qiang Yang

is this you? claim profile

∙ 0 followers
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

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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
Graph Random Neural Network

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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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. ∙ 32 ∙ share

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
Federated Reinforcement Learning

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

read it
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

read it
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

read it
Building Ethics into Artificial Intelligence

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

read it
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

read it
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

read it
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

read it
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

read it
Learning to Multitask

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

read it
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

read it
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

read it
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

read it
Crowd Flow Prediction by Deep Spatio-Temporal Transfer Learning

Crowd flow prediction is a fundamental urban computing problem. Recently...
02/01/2018 ∙ by Leye Wang, et al. ∙ 0 ∙ share

read it
Data Dwarfs: A Lens Towards Fully Understanding Big Data and AI Workloads

The complexity and diversity of big data and AI workloads make understan...
02/01/2018 ∙ by Wanling Gao, et al. ∙ 0 ∙ share

read it
Big Data Dwarfs: Towards Fully Understanding Big Data Analytics Workloads

Though the big data benchmark suites like BigDataBench and CloudSuite ha...
02/01/2018 ∙ by Wanling Gao, et al. ∙ 0 ∙ share

read it
Fine Grained Knowledge Transfer for Personalized Task-oriented Dialogue Systems

Training a personalized dialogue system requires a lot of data, and the ...
11/11/2017 ∙ by Kaixiang Mo, et al. ∙ 0 ∙ share

read it
Integrating User and Agent Models: A Deep Task-Oriented Dialogue System

Task-oriented dialogue systems can efficiently serve a large number of c...
11/10/2017 ∙ by Weiyan Wang, et al. ∙ 0 ∙ share

read it
A Dwarf-based Scalable Big Data Benchmarking Methodology

Different from the traditional benchmarking methodology that creates a n...
11/09/2017 ∙ by Wanling Gao, et al. ∙ 0 ∙ share

read it

Qiang Yang

Featured Co-authors