Xiujun Li
Xiujun Li
Computer Science and Engineering, University of Washington, Microsoft Research
Email verificata su microsoft.com
Citata da
Citata da
End-to-End Task-Completion Neural Dialogue Systems
X Li, YN Chen, L Li, J Gao, A Celikyilmaz
The 8th International Joint Conference on Natural Language Processing …, 2017
Towards end-to-end reinforcement learning of dialogue agents for information access
B Dhingra, L Li, X Li, J Gao, YN Chen, F Ahmed, L Deng
arXiv preprint arXiv:1609.00777, 2016
Advances in smartphone-based point-of-care diagnostics
X Xu, A Akay, H Wei, SQ Wang, B Pingguan-Murphy, BE Erlandsson, ...
Proceedings of the IEEE 103 (2), 236-247, 2015
Bbq-networks: Efficient exploration in deep reinforcement learning for task-oriented dialogue systems
Z Lipton, X Li, J Gao, L Li, F Ahmed, L Deng
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Composite task-completion dialogue policy learning via hierarchical deep reinforcement learning
B Peng, X Li, L Li, J Gao, A Celikyilmaz, S Lee, KF Wong
arXiv preprint arXiv:1704.03084, 2017
Generating informative and diverse conversational responses via adversarial information maximization
Y Zhang, M Galley, J Gao, Z Gan, X Li, C Brockett, B Dolan
Advances in Neural Information Processing Systems, 1810-1820, 2018
A user simulator for task-completion dialogues
X Li, ZC Lipton, B Dhingra, L Li, J Gao, YN Chen
arXiv preprint arXiv:1612.05688, 2016
Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning
Z Yao, X Li, J Gao, B Sadler, H Sun
arXiv preprint arXiv:1808.06740, 2018
Deep dyna-q: Integrating planning for task-completion dialogue policy learning
B Peng, X Li, J Gao, J Liu, KF Wong, SY Su
arXiv preprint arXiv:1801.06176, 2018
End-to-end joint learning of natural language understanding and dialogue manager
X Yang, YN Chen, D Hakkani-Tür, P Crook, X Li, J Gao, L Deng
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
Recurrent reinforcement learning: a hybrid approach
X Li, L Li, J Gao, X He, J Chen, L Deng, J He
arXiv preprint arXiv:1509.03044, 2015
Switch-based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning
Y Wu, X Li, J Liu, J Gao, Y Yang
AAAI 2019, 2019
Tactical rewind: Self-correction via backtracking in vision-and-language navigation
L Ke, X Li, Y Bisk, A Holtzman, Z Gan, J Liu, J Gao, Y Choi, S Srinivasa
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
Convlab: Multi-domain end-to-end dialog system platform
S Lee, Q Zhu, R Takanobu, X Li, Y Zhang, Z Zhang, J Li, B Peng, X Li, ...
arXiv preprint arXiv:1904.08637, 2019
Discriminative deep dyna-q: Robust planning for dialogue policy learning
SY Su, X Li, J Gao, J Liu, YN Chen
arXiv preprint arXiv:1808.09442, 2018
Subgoal discovery for hierarchical dialogue policy learning
D Tang, X Li, J Gao, C Wang, L Li, T Jebara
arXiv preprint arXiv:1804.07855, 2018
Devices and methods for multiplexed assays
GM Whitesides, KA Mirica, AW Martinez, C Cheng, ST Phillips, ...
US Patent 8,821,810, 2014
Adversarial advantage actor-critic model for task-completion dialogue policy learning
B Peng, X Li, J Gao, J Liu, YN Chen, KF Wong
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
Joint language understanding and dialogue management using binary classification based on forward and backward recurrent neural network
X Li, PA Crook, L Deng, J Gao, YN Chen, X Yang
US Patent 10,268,679, 2019
Sparse and low-rank coupling image segmentation model via nonconvex regularization
X Zhang, C Xu, M Li, X Sun
International Journal of Pattern Recognition and Artificial Intelligence 29 …, 2015
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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