Bei Jiang
According to our database1,
Bei Jiang
authored at least 37 papers
between 2016 and 2024.
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Bibliography
2024
Comput. Stat., June, 2024
GHGPR-PPIS: A graph convolutional network for identifying protein-protein interaction site using heat kernel with Generalized PageRank techniques and edge self-attention feature processing block.
Comput. Biol. Medicine, January, 2024
MMDTA: A Multimodal Deep Model for Drug-Target Affinity with a Hybrid Fusion Strategy.
J. Chem. Inf. Model., 2024
Debiasing with Sufficient Projection: A General Theoretical Framework for Vector Representations.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024
Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Sci. China Inf. Sci., June, 2023
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
The Sufficiency of Off-Policyness and Soft Clipping: PPO Is Still Insufficient according to an Off-Policy Measure.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Rapid Repurposing of Novel Combination Drugs for the Treatment of Heart Failure via a Computationally Guided Network Screening Approach.
J. Chem. Inf. Model., 2022
Frontiers Big Data, 2022
Associations between Longitudinal Gestational Weight Gain and Scalar Infant Birth Weight: A Bayesian Joint Modeling Approach.
Entropy, 2022
How Does Value Distribution in Distributional Reinforcement Learning Help Optimization?
CoRR, 2022
Sigmoidally Preconditioned Off-policy Learning: a new exploration method for reinforcement learning.
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
ACM Trans. Knowl. Discov. Data, 2021
Comput. Stat., 2021
Towards Understanding Distributional Reinforcement Learning: Regularization, Optimization, Acceleration and Sinkhorn Algorithm.
CoRR, 2021
Proceedings of the WWW '21: The Web Conference 2021, 2021
Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
Sparse Multicategory Generalized Distance Weighted Discrimination in Ultra-High Dimensions.
Entropy, 2020
2019
Sparse wavelet estimation in quantile regression with multiple functional predictors.
Comput. Stat. Data Anal., 2019
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019
2018
CoRR, 2018
Int. J. Appl. Math. Comput. Sci., 2018
2017
Neurocomputing, 2017
Proceedings of the Neural Information Processing - 24th International Conference, 2017
2016
Proceedings of the Cognitive Systems and Signal Processing, 2016