Yatao Bian
Orcid: 0000-0002-2368-4084Affiliations:
- Tencent AI Lab, China
- ETH Zürich, Department of Computer Science, Switzerland
According to our database1,
Yatao Bian
authored at least 82 papers
between 2012 and 2024.
Collaborative distances:
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Bibliography
2024
IEEE Trans. Pattern Anal. Mach. Intell., March, 2024
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations.
CoRR, 2024
Integration of cognitive tasks into artificial general intelligence test for large models.
CoRR, 2024
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024
2023
Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes.
CoRR, 2023
CoRR, 2023
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators.
CoRR, 2023
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
CoRR, 2022
Can Pre-trained Models Really Learn Better Molecular Representations for AI-aided Drug Discovery?
CoRR, 2022
CoRR, 2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection.
CoRR, 2022
DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup.
CoRR, 2022
Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs.
CoRR, 2022
Learning Set Functions Under the Optimal Subset Oracle via Equivariant Variational Inference.
CoRR, 2022
Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift.
CoRR, 2022
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations.
CoRR, 2022
Bioinform., 2022
Divide-and-Conquer: Post-User Interaction Network for Fake News Detection on Social Media.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022
Proceedings of the Topological, 2022
Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022
2021
Generalization Bounds for Stochastic Gradient Langevin Dynamics: A Unified View via Information Leakage Analysis.
CoRR, 2021
Energy-Based Learning for Cooperative Games, with Applications to Feature/Data/Model Valuations.
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
2020
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models.
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
PhD thesis, 2019
Parallel Coordinate Descent Newton Method for Efficient L<sub>1</sub> -Regularized Loss Minimization.
IEEE Trans. Neural Networks Learn. Syst., 2019
CoRR, 2019
Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference.
Proceedings of the 36th International Conference on Machine Learning, 2019
2018
Optimal DR-Submodular Maximization and Applications to Provable Mean Field Inference.
CoRR, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the Pattern Recognition - 39th German Conference, 2017
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
2016
Proceedings of the 2016 Information Theory and Applications Workshop, 2016
2015
Proceedings of the 2015 IEEE Information Theory Workshop, 2015
2013
Digitize Your Body and Action in 3-D at Over 10 FPS: Real Time Dense Voxel Reconstruction and Marker-less Motion Tracking via GPU Acceleration.
CoRR, 2013
CoRR, 2013
Bundle CDN: A Highly Parallelized Approach for Large-Scale ℓ1-Regularized Logistic Regression.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013
2012
Parallelized Annealed Particle Filter for real-time marker-less motion tracking via heterogeneous computing.
Proceedings of the 21st International Conference on Pattern Recognition, 2012