受强制性开放获取政策约束的文章 - Lei Han了解详情
无法在其他位置公开访问的文章：3 篇
Temporal causal inference with time lag
S Du, G Song, L Han, H Hong
Neural computation 30 (1), 271-291, 2017
强制性开放获取政策： 国家自然科学基金委员会
Structure feature learning method for incomplete data
X Zhou, X Xing, L Han, H Hong, K Bian, K Xie
International Journal of Pattern Recognition and Artificial Intelligence 30 …, 2016
强制性开放获取政策： 国家自然科学基金委员会
The Fittest Wins: A Multistage Framework Achieving New SOTA in ViZDoom Competition
S Li, J Xu, H Dong, Y Yang, C Yuan, P Sun, L Han
IEEE Transactions on Games 16 (1), 225-234, 2023
强制性开放获取政策： 国家自然科学基金委员会
可在其他位置公开访问的文章：21 篇
Rorl: Robust offline reinforcement learning via conservative smoothing
R Yang, C Bai, X Ma, Z Wang, C Zhang, L Han
Advances in neural information processing systems 35, 23851-23866, 2022
强制性开放获取政策： 国家自然科学基金委员会
Learning multi-level task groups in multi-task learning
L Han, Y Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
强制性开放获取政策： 国家自然科学基金委员会
Learning tree structure in multi-task learning
L Han, Y Zhang
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015
强制性开放获取政策： 国家自然科学基金委员会
Multi-Stage Multi-Task Learning with Reduced Rank
L Han, Y Zhang
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016
强制性开放获取政策： 国家自然科学基金委员会
Principled exploration via optimistic bootstrapping and backward induction
C Bai, L Wang, L Han, J Hao, A Garg, P Liu, Z Wang
International Conference on Machine Learning, 577-587, 2021
强制性开放获取政策： 国家自然科学基金委员会
Local uncertainty sampling for large-scale multiclass logistic regression
L Han, KM Tan, T Yang, T Zhang
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
Encoding tree sparsity in multi-task learning: A probabilistic framework
L Han, Y Zhang, G Song, K Xie
Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014
强制性开放获取政策： 国家自然科学基金委员会
Graph-guided multi-task sparse learning model: a method for identifying antigenic variants of influenza A (H3N2) virus
L Han, L Li, F Wen, L Zhong, T Zhang, XF Wan
Bioinformatics 35 (1), 77-87, 2019
强制性开放获取政策： US National Institutes of Health
Variational dynamic for self-supervised exploration in deep reinforcement learning
C Bai, P Liu, K Liu, L Wang, Y Zhao, L Han, Z Wang
IEEE Transactions on neural networks and learning systems 34 (8), 4776-4790, 2021
强制性开放获取政策： 国家自然科学基金委员会
Multi-task learning sparse group lasso: a method for quantifying antigenicity of influenza A (H1N1) virus using mutations and variations in glycosylation of Hemagglutinin
L Li, D Chang, L Han, X Zhang, J Zaia, XF Wan
BMC bioinformatics 21, 1-22, 2020
强制性开放获取政策： US National Institutes of Health
Discriminative feature grouping
L Han, Y Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
强制性开放获取政策： 国家自然科学基金委员会
Bayesian model averaging with exponentiated least squares loss
D Dai, L Han, T Yang, T Zhang
IEEE Transactions on Information Theory 64 (5), 3331-3345, 2018
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent
Y Li, J Xu, L Han, ZQ Luo
Forty-first International Conference on Machine Learning, 2024
强制性开放获取政策： 国家自然科学基金委员会
Reduction Techniques for Graph-based Convex Clustering
L Han, Y Zhang
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016
强制性开放获取政策： 国家自然科学基金委员会
Generalized Hierarchical Sparse Model for Arbitrary-Order Interactive Antigenic Sites Identification in Flu Virus Data
L Han, Y Zhang, XF Wan, T Zhang
Proceedings of the 22nd ACM SIGKDD Conference on Knowledge Discovery and …, 2016
强制性开放获取政策： US National Science Foundation, US National Institutes of Health, 国家自然科 …
Overlapping decomposition for Gaussian graphical modeling
G Song, L Han, K Xie
IEEE Transactions on Knowledge and Data Engineering 27 (8), 2217-2230, 2015
强制性开放获取政策： 国家自然科学基金委员会
Hierarchical multiagent reinforcement learning for allocating guaranteed display ads
L Wang, L Han, X Chen, C Li, J Huang, W Zhang, W Zhang, X He, D Luo
IEEE Transactions on Neural Networks and Learning Systems 33 (10), 5361-5373, 2021
强制性开放获取政策： 国家自然科学基金委员会
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