Jiashuo Liu
Jiashuo Liu
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Towards out-of-distribution generalization: A survey
J Liu, Z Shen, Y He, X Zhang, R Xu, H Yu, P Cui
arXiv preprint arXiv:2108.13624, 2023
Heterogeneous risk minimization
J Liu, Z Hu, P Cui, B Li, Z Shen
International Conference on Machine Learning, 6804-6814, 2021
Stable learning via differentiated variable decorrelation
Z Shen, P Cui, J Liu, T Zhang, B Li, Z Chen
Proceedings of the 26th acm sigkdd international conference on knowledge …, 2020
Triple generative adversarial networks
C Li, K Xu, J Zhu, J Liu, B Zhang
IEEE transactions on pattern analysis and machine intelligence 44 (12), 9629 …, 2021
Invariant preference learning for general debiasing in recommendation
Z Wang, Y He, J Liu, W Zou, PS Yu, P Cui
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
Kernelized heterogeneous risk minimization
J Liu, Z Hu, P Cui, B Li, Z Shen
arXiv preprint arXiv:2110.12425, 2021
Stable adversarial learning under distributional shifts
J Liu, Z Shen, P Cui, L Zhou, K Kuang, B Li, Y Lin
Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 8662-8670, 2021
Signed graph neural network with latent groups
H Liu, Z Zhang, P Cui, Y Zhang, Q Cui, J Liu, W Zhu
Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021
Towards domain generalization in object detection
X Zhang, Z Xu, R Xu, J Liu, P Cui, W Wan, C Sun, C Li
arXiv preprint arXiv:2203.14387, 2022
Distributionally robust learning with stable adversarial training
J Liu, Z Shen, P Cui, L Zhou, K Kuang, B Li
IEEE Transactions on Knowledge and Data Engineering, 2022
Distributionally robust optimization with data geometry
J Liu, J Wu, B Li, P Cui
Advances in neural information processing systems 35, 33689-33701, 2022
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets
J Liu, T Wang, P Cui, H Namkoong
NeurIPS 2023, Dataset and Benchmark Track, 2023
Offline policy evaluation in large action spaces via outcome-oriented action grouping
J Peng, H Zou, J Liu, S Li, Y Jiang, J Pei, P Cui
Proceedings of the ACM Web Conference 2023, 1220-1230, 2023
Towards the ultimate PMT waveform analysis for neutrino and dark matter experiments
DC Xu, BD Xu, EJ Bao, YY Wu, AQ Zhang, YY Wang, GL Zhang, Y Xu, ...
Journal of Instrumentation 17 (06), P06040, 2022
Bridging the gap: neural collapse inspired prompt tuning for generalization under class imbalance
D Zhu, Y Li, M Zhang, J Yuan, J Liu, K Kuang, C Wu
arXiv preprint arXiv:2306.15955, 2023
Measure the Predictive Heterogeneity
J Liu, J Wu, R Pi, R Xu, X Zhang, B Li, P Cui
The Eleventh International Conference on Learning Representations, 2023
Enhancing Distributional Stability among Sub-populations
J Liu, J Wu, J Peng, X Wu, Y Zheng, B Li, P Cui
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2024
Rethinking the Evaluation Protocol of Domain Generalization
H Yu, X Zhang, R Xu, J Liu, Y He, P Cui
arXiv preprint arXiv:2305.15253, 2023
Meta Adaptive Task Sampling for Few-Domain Generalization
Z Shen, H Yu, P Cui, J Liu, X Zhang, L Zhou, F Liu
arXiv preprint arXiv:2305.15644, 2023
Exploring and Exploiting Data Heterogeneity in Recommendation
Z Wang, J Liu, H Zou, X Zhang, Y He, D Liang, P Cui
arXiv preprint arXiv:2305.15431, 2023
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