2025
COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts.
CoRR, April, 2025

AdaptSel: Adaptive Selection of Biased and Debiased Recommendation Models for Varying Test Environments.
ACM Trans. Knowl. Discov. Data, February, 2025

Sample Weight Averaging for Stable Prediction.
CoRR, February, 2025

Error Slice Discovery via Manifold Compactness.
CoRR, January, 2025

EvoPath: Evolutionary meta-path discovery with large language models for complex heterogeneous information networks.
Inf. Process. Manag., 2025

2024
Stable Cox regression for survival analysis under distribution shifts.
Nat. Mac. Intell., 2024

Model-Agnostic Random Weighting for Out-of-Distribution Generalization.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Domain-wise Data Acquisition to Improve Performance under Distribution Shift.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Rethinking the Evaluation Protocol of Domain Generalization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Exploring and Exploiting Data Heterogeneity in Recommendation.
CoRR, 2023

NICO++: Towards Better Benchmarking for Domain Generalization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Stable Learning via Sparse Variable Independence.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Covariate-Shift Generalization via Random Sample Weighting.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Distilling Causal Metaknowledge from Knowledge Graphs.
IEEE Data Eng. Bull., 2022

CausPref: Causal Preference Learning for Out-of-Distribution Recommendation.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Invariant Preference Learning for General Debiasing in Recommendation.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

NICO Challenge: Out-of-Distribution Generalization for Image Recognition Challenges.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

2021
Towards Non-I.I.D. image classification: A dataset and baselines.
Pattern Recognit., 2021

Towards Out-Of-Distribution Generalization: A Survey.
CoRR, 2021

Purify and Generate: Learning Faithful Item-to-Item Graph from Noisy User-Item Interaction Behaviors.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

DARING: Differentiable Causal Discovery with Residual Independence.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Deep Stable Learning for Out-of-Distribution Generalization.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Counterfactual Prediction for Bundle Treatment.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Stable Graphs from Multiple Environments with Selection Bias.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019
NICO: A Dataset Towards Non-I.I.D. Image Classification.
CoRR, 2019

2018
Progressive Generative Hashing for Image Retrieval.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018