Yang Liu

Orcid: 0000-0003-3800-3533

Affiliations:
  • Tsinghua University, Institute for AI Industry Research, Beijing, China
  • WeBank, AI Department, Shenzhen, China (former)
  • Princeton University, NJ, USA (PhD)


According to our database1, Yang Liu authored at least 110 papers between 2016 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Vertical Federated Learning: Concepts, Advances, and Challenges.
IEEE Trans. Knowl. Data Eng., July, 2024

AQUILA: Communication Efficient Federated Learning With Adaptive Quantization in Device Selection Strategy.
IEEE Trans. Mob. Comput., June, 2024

SAFARI: Sparsity-Enabled Federated Learning With Limited and Unreliable Communications.
IEEE Trans. Mob. Comput., May, 2024

FedHAP: Federated Hashing With Global Prototypes for Cross-Silo Retrieval.
IEEE Trans. Parallel Distributed Syst., April, 2024

A Federated Learning Framework Based on Differentially Private Continuous Data Release.
IEEE Trans. Dependable Secur. Comput., 2024

A mechanism design approach for multi-party machine learning.
Theor. Comput. Sci., 2024

Autonomous Driving in Unstructured Environments: How Far Have We Come?
CoRR, 2024

Enhancing Parameter Efficiency and Generalization in Large-Scale Models: A Regularized and Masked Low-Rank Adaptation Approach.
CoRR, 2024

Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Physical Dynamics Learning.
CoRR, 2024

FL-TAC: Enhanced Fine-Tuning in Federated Learning via Low-Rank, Task-Specific Adapter Clustering.
CoRR, 2024

Weakly Supervised Anomaly Detection via Knowledge-Data Alignment.
Proceedings of the ACM on Web Conference 2024, 2024

Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Broad Physical Dynamics Learning.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

VFLAIR: A Research Library and Benchmark for Vertical Federated Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

OpenChat: Advancing Open-source Language Models with Mixed-Quality Data.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Federated PAC-Bayesian Learning on Non-IID Data.
Proceedings of the IEEE International Conference on Acoustics, 2024

A Weakly Supervised Part Detection Method for Robust Fine-Grained Classification.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

2023
A multimodal approach for improving market price estimation in online advertising.
Knowl. Based Syst., April, 2023

CAreFL: Enhancing smart healthcare with Contribution-Aware Federated Learning.
AI Mag., March, 2023

Towards efficient communications in federated learning: A contemporary survey.
J. Frankl. Inst., 2023

Federated Learning without Full Labels: A Survey.
IEEE Data Eng. Bull., 2023

Mutual Enhancement of Large and Small Language Models with Cross-Silo Knowledge Transfer.
CoRR, 2023

VFLAIR: A Research Library and Benchmark for Vertical Federated Learning.
CoRR, 2023

Federated PAC-Bayesian Learning on Non-IID data.
CoRR, 2023

Physics-Inspired Neural Graph ODE for Long-term Dynamical Simulation.
CoRR, 2023

AQUILA: Communication Efficient Federated Learning with Adaptive Quantization of Lazily-Aggregated Gradients.
CoRR, 2023

AIGC Empowering Telecom Sector White Paper_chinese.
CoRR, 2023

Eliminating Label Leakage in Tree-Based Vertical Federated Learning.
CoRR, 2023

6G Network Business Support System.
CoRR, 2023

6G Network Operation Support System.
CoRR, 2023

PerFedRec++: Enhancing Personalized Federated Recommendation with Self-Supervised Pre-Training.
CoRR, 2023

Federated Learning without Full Labels: A Survey.
CoRR, 2023

Deep Insights into Noisy Pseudo Labeling on Graph Data.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Hierarchical Knowledge Transfer Framework for Heterogeneous Federated Learning.
Proceedings of the IEEE INFOCOM 2023, 2023

Multimodal Federated Learning via Contrastive Representation Ensemble.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Inclusive Data Representation in Federated Learning: A Novel Approach Integrating Textual and Visual Prompt.
Proceedings of the Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing, 2023

Breaching FedMD: Image Recovery via Paired-Logits Inversion Attack.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Modeling Adversarial Attack on Pre-trained Language Models as Sequential Decision Making.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Human Mobility Modeling during the COVID-19 Pandemic via Deep Graph Diffusion Infomax.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Inspecting the Running Process of Horizontal Federated Learning via Visual Analytics.
IEEE Trans. Vis. Comput. Graph., 2022

FedBCD: A Communication-Efficient Collaborative Learning Framework for Distributed Features.
IEEE Trans. Signal Process., 2022

Customized Federated Learning for Multi-Source Decentralized Medical Image Classification.
IEEE J. Biomed. Health Informatics, 2022

Preface to Federated Learning: Algorithms, Systems, and Applications: Part 2.
ACM Trans. Intell. Syst. Technol., 2022

Introduction to the Special Issue on the Federated Learning: Algorithms, Systems, and Applications: Part 1.
ACM Trans. Intell. Syst. Technol., 2022

Communication-Efficient Federated Learning with Adaptive Quantization.
ACM Trans. Intell. Syst. Technol., 2022

GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learning.
ACM Trans. Intell. Syst. Technol., 2022

FedCVT: Semi-supervised Vertical Federated Learning with Cross-view Training.
ACM Trans. Intell. Syst. Technol., 2022

Semi-Supervised Federated Heterogeneous Transfer Learning.
Knowl. Based Syst., 2022

Vertical Federated Learning.
CoRR, 2022

Towards Communication Efficient and Fair Federated Personalized Sequential Recommendation.
CoRR, 2022

Brisk-Yolo: A Lightweight Object Detection Algorithm for Edge Devices.
Proceedings of the IEEE Smartworld, 2022

TailorFL: Dual-Personalized Federated Learning under System and Data Heterogeneity.
Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems, 2022

Privacy-Preserving Federated Cross-Domain Social Recommendation.
Proceedings of the Trustworthy Federated Learning - First International Workshop, 2022

Federated Capsule Graph Neural Network with Personalization.
Proceedings of the Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers, 2022

Adversarial Contrastive Learning via Asymmetric InfoNCE.
Proceedings of the Computer Vision - ECCV 2022, 2022


Contribution-Aware Federated Learning for Smart Healthcare.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data.
IEEE Trans. Signal Process., 2021

StarFL: Hybrid Federated Learning Architecture for Smart Urban Computing.
ACM Trans. Intell. Syst. Technol., 2021

FATE: An Industrial Grade Platform for Collaborative Learning With Data Protection.
J. Mach. Learn. Res., 2021

Advances and Open Problems in Federated Learning.
Found. Trends Mach. Learn., 2021

SecureBoost: A Lossless Federated Learning Framework.
IEEE Intell. Syst., 2021

Defending Label Inference and Backdoor Attacks in Vertical Federated Learning.
CoRR, 2021

Privacy-preserving Federated Adversarial Domain Adaption over Feature Groups for Interpretability.
CoRR, 2021

FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning.
CoRR, 2021

Self-supervised Cross-silo Federated Neural Architecture Search.
CoRR, 2021

Federated Learning-Powered Visual Object Detection for Safety Monitoring.
AI Mag., 2021

Deconvolutional Networks on Graph Data.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
A Gamified Research Tool for Incentive Mechanism Design in Federated Learning.
Proceedings of the Federated Learning - Privacy and Incentive, 2020

A Construction of Optimal Frequency Hopping Sequence Set via Combination of Multiplicative and Additive Groups of Finite Fields.
IEEE Trans. Inf. Theory, 2020

Multi-component transfer metric learning for handling unrelated source domain samples.
Knowl. Based Syst., 2020

A Sustainable Incentive Scheme for Federated Learning.
IEEE Intell. Syst., 2020

Introduction to the Special Issue on Federated Machine Learning.
IEEE Intell. Syst., 2020

A Secure Federated Transfer Learning Framework.
IEEE Intell. Syst., 2020

SAG-GAN: Semi-Supervised Attention-Guided GANs for Data Augmentation on Medical Images.
CoRR, 2020

FedMVT: Semi-supervised Vertical Federated Learning with MultiView Training.
CoRR, 2020

A VCG-based Fair Incentive Mechanism for Federated Learning.
CoRR, 2020

FedML: A Research Library and Benchmark for Federated Machine Learning.
CoRR, 2020

Backdoor attacks and defenses in feature-partitioned collaborative learning.
CoRR, 2020

Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention.
CoRR, 2020

FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data.
CoRR, 2020

A Survey towards Federated Semi-supervised Learning.
CoRR, 2020

Learning to Detect Malicious Clients for Robust Federated Learning.
CoRR, 2020

Mechanism Design for Multi-Party Machine Learning.
CoRR, 2020

Federated learning for privacy-preserving AI.
Commun. ACM, 2020

Addressing the Challenges of Government Service Provision with AI.
AI Mag., 2020

BatchCrypt: Efficient Homomorphic Encryption for Cross-Silo Federated Learning.
Proceedings of the 2020 USENIX Annual Technical Conference, 2020

A Multi-player Game for Studying Federated Learning Incentive Schemes.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Federated Transfer Learning for EEG Signal Classification.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

RPN: A Residual Pooling Network for Efficient Federated Learning.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

A Fairness-aware Incentive Scheme for Federated Learning.
Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

FedVision: An Online Visual Object Detection Platform Powered by Federated Learning.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Federated Learning
Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers, ISBN: 978-3-031-01585-4, 2019

Federated Machine Learning: Concept and Applications.
ACM Trans. Intell. Syst. Technol., 2019

A Communication Efficient Vertical Federated Learning Framework.
CoRR, 2019

Advances and Open Problems in Federated Learning.
CoRR, 2019

Reviewing and Improving the Gaussian Mechanism for Differential Privacy.
CoRR, 2019

Real-World Image Datasets for Federated Learning.
CoRR, 2019

Abnormal Client Behavior Detection in Federated Learning.
CoRR, 2019

Federated Transfer Reinforcement Learning for Autonomous Driving.
CoRR, 2019

HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography.
CoRR, 2019

SecureBoost: A Lossless Federated Learning Framework.
CoRR, 2019

A Revenue-Maximizing Bidding Strategy for Demand-Side Platforms.
IEEE Access, 2019

Multi-Agent Visualization for Explaining Federated Learning.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Fair and Explainable Dynamic Engagement of Crowd Workers.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Secure and Efficient Federated Transfer Learning.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Privacy-preserving Heterogeneous Federated Transfer Learning.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018
An automatically vetting mechanism for SSL error-handling vulnerability in android hybrid Web apps.
World Wide Web, 2018

Secure Federated Transfer Learning.
CoRR, 2018

2016
SpatialGraphx: A Distributed Graph Computing Framework for Spatial and Temporal Data at Scale.
Proceedings of the 40th IEEE Annual Computer Software and Applications Conference, 2016


  Loading...