We stand with Ukraine

We stand with Ukraine

Xiaoli Tang

Orcid: 0000-0002-1967-2953

Affiliations:

Nanyang Technological University, School of Computer Science and Engineering, Singapore

According to our database¹, Xiaoli Tang authored at least 38 papers between 2019 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Links

Online presence:

on orcid.org

On csauthors.net:

Bibliography

2026

Efficient Federated Learning With Mean Block Difference-Based Global Aggregation and Patience-Based Local Training.

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IEEE Trans. Knowl. Data Eng., July, 2026

Advances and Open Challenges in Federated Foundation Models.

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Alysa Ziying Tan

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IEEE Commun. Surv. Tutorials, 2026

FedDiG: Frequency-Guided Diffusion Diversity for Generalizable Federated Time Series Classification.

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Proceedings of the ACM Web Conference 2026, 2026

FL@FM-TheWebConf'26: The 3rd International Workshop on Federated Foundation Models for the Web.

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Proceedings of the Companion Proceedings of the ACM Web Conference 2026, 2026

2025

A Cost-Aware Utility-Maximizing Bidding Strategy for Auction-Based Federated Learning.

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IEEE Trans. Neural Networks Learn. Syst., July, 2025

Ten Challenging Problems in Federated Foundation Models.

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IEEE Trans. Knowl. Data Eng., July, 2025

Towards Trustworthy AI-Empowered Real-Time Bidding for Online Advertisement Auctioning.

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ACM Comput. Surv., June, 2025

Fairness-Aware Reverse Auction-Based Federated Learning.

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IEEE Internet Things J., April, 2025

A Reinforcement Learning-based Bidding Strategy for Data Consumers in Auction-based Federated Learning.

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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Efficient Heterogeneity-Aware Federated Active Data Selection.

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Sheng-Jun Huang

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Proceedings of the Forty-second International Conference on Machine Learning, 2025

Multi-Session Budget Optimization for Forward Auction-based Federated Learning.

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Proceedings of the Forty-second International Conference on Machine Learning, 2025

Reputation-aware Revenue Allocation for Auction-based Federated Learning.

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Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

MuLAN: Multi-level attention-enhanced matching network for few-shot knowledge graph completion.

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Neural Networks, 2024

Efficient Large-Scale Personalizable Bidding for Multiagent Auction-Based Federated Learning.

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IEEE Internet Things J., 2024

Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated Learning.

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CoRR, 2024

Advances and Open Challenges in Federated Learning with Foundation Models.

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Alysa Ziying Tan

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CoRR, 2024

Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning.

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Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Multi-Session Multi-Objective Budget Optimization for Auction-based Federated Learning.

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Proceedings of the International Joint Conference on Neural Networks, 2024

Modeling Time Decay Effect in Temporal Knowledge Graphs via Multivariate Hawkes Process.

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Proceedings of the International Joint Conference on Neural Networks, 2024

Stakeholder-oriented Decision Support for Auction-based Federated Learning.

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Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Dual Calibration-based Personalised Federated Learning.

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Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

A Bias-Free Revenue-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning.

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Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Intelligent Agents for Auction-based Federated Learning: A Survey.

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Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler.

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Proceedings of the Forty-first International Conference on Machine Learning, 2024

Agent-Oriented Joint Decision Support for Data Owners in Auction-Based Federated Learning.

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Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

FedRMS: Privacy-Preserving Federated Knowledge Graph Embedding Through Randomization.

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Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

HiFi-Gas: Hierarchical Federated Learning Incentive Mechanism Enhanced Gas Usage Estimation.

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Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

IBCA: An Intelligent Platform for Social Insurance Benefit Qualification Status Assessment.

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Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Capsule neural tensor networks with multi-aspect information for Few-shot Knowledge Graph Completion.

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Neural Networks, July, 2023

Dynamically Optimizing Display Advertising Profits Under Diverse Budget Settings.

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IEEE Trans. Knowl. Data Eng., 2023

Multi-Session Budget Optimization for Forward Auction-based Federated Learning.

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CoRR, 2023

Hierarchical Federated Learning Incentivization for Gas Usage Estimation.

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CoRR, 2023

Competitive-Cooperative Multi-Agent Reinforcement Learning for Auction-based Federated Learning.

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Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Utility-Maximizing Bidding Strategy for Data Consumers in Auction-Based Federated Learning.

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Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

2022

Kaplan-Meier Markov network: Learning the distribution of market price by censored data in online advertising.

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Knowl. Based Syst., 2022

2021

Multi-task Learning for Bias-Free Joint CTR Prediction and Market Price Modeling in Online Advertising.

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Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Timespan-Aware Dynamic Knowledge Graph Embedding by Incorporating Temporal Evolution.

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IEEE Access, 2020

2019

Unifying Task-Oriented Knowledge Graph Learning and Recommendation.

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IEEE Access, 2019

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