Jian Liang

Orcid: 0000-0001-5352-0278

Affiliations:
  • Alibaba Group, AI for international Department, Beijing, China (2020 - 2022)
  • Tencent, Cloud and Smart Industries Group, Wireless Security Products Department, China (2018 - 2020)
  • Tsinghua University, Beijing National Research Center for Information Science and Technology (BNRist), Department of Automation, Institute for Artificial Intelligence, State Key Lab of Intelligent Technologies and Systems, Beijing, China (PhD 2018)


According to our database1, Jian Liang authored at least 35 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction.
CoRR, 2024

CLAP: Collaborative Adaptation for Patchwork Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Meta-Reweighted Regularization for Unsupervised Domain Adaptation.
IEEE Trans. Knowl. Data Eng., March, 2023

Improving Generalization with Domain Convex Game.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Model-Protected Multi-Task Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Adversarial Filtering Modeling on Long-term User Behavior Sequences for Click-Through Rate Prediction.
CoRR, 2022

Adversarial Filtering Modeling on Long-term User Behavior Sequences for Click-Through Rate Prediction.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Synergy-of-Experts: Collaborate to Improve Adversarial Robustness.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Collaboration Equilibrium in Federated Learning.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

ACE: A Coarse-to-Fine Learning Framework for Reliable Representation Learning Against Label Noise.
Proceedings of the International Joint Conference on Neural Networks, 2022

Causality Inspired Representation Learning for Domain Generalization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Dynamic Hypergraph Learning for Collaborative Filtering.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
Robust Few-Shot Learning for User-Provided Data.
IEEE Trans. Neural Networks Learn. Syst., 2021

Incentive Compatible Pareto Alignment for Multi-Source Large Graphs.
CoRR, 2021

Fair and Consistent Federated Learning.
CoRR, 2021

Learning to Collaborate.
CoRR, 2021

Pareto Domain Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Policy-Driven Attack: Learning to Query for Hard-label Black-box Adversarial Examples.
Proceedings of the 9th International Conference on Learning Representations, 2021

Semantic Concentration for Domain Adaptation.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Relation-Guided Representation Learning.
Neural Networks, 2020

Reliable Evaluations for Natural Language Inference based on a Unified Cross-dataset Benchmark.
CoRR, 2020

Domain Agnostic Learning for Unbiased Authentication.
CoRR, 2020

Hybrid Differentially Private Federated Learning on Vertically Partitioned Data.
CoRR, 2020

Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019
Additive Adversarial Learning for Unbiased Authentication.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Leveraging mixed and incomplete outcomes via reduced-rank modeling.
J. Multivar. Anal., 2018

Robust finite mixture regression for heterogeneous targets.
Data Min. Knowl. Discov., 2018

2017
Weakly- and Semi-Supervised Object Detection with Expectation-Maximization Algorithm.
CoRR, 2017

An RNN Architecture with Dynamic Temporal Matching for Personalized Predictions of Parkinson's Disease.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

2016
DeepFish: Accurate underwater live fish recognition with a deep architecture.
Neurocomputing, 2016

Poster Paper: Predicting Seizures from Electroencephalography Recordings: A Knowledge Transfer Strategy.
Proceedings of the 2016 IEEE International Conference on Healthcare Informatics, 2016

Predicting Seizures from Electroencephalography Recordings: A Knowledge Transfer Strategy.
Proceedings of the 2016 IEEE International Conference on Healthcare Informatics, 2016


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