Yuexin Wu
Yuexin Wu
Google Tensorflow; Carnegie Mellon University
Verified email at - Homepage
Cited by
Cited by
Deep Learning for Extreme Multi-label Text Classification
J Liu, WC Chang, Y Wu, Y Yang
Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017
Analogical inference for multi-relational embeddings
H Liu, Y Wu, Y Yang
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
Review networks for caption generation
Z Yang, Y Yuan, Y Wu, WW Cohen, RR Salakhutdinov
Advances in Neural Information Processing Systems, 2361-2369, 2016
Storygan: A sequential conditional gan for story visualization
Y Li, Z Gan, Y Shen, J Liu, Y Cheng, Y Wu, L Carin, D Carlson, J Gao
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
Deep learning for epidemiological predictions
Y Wu, Y Yang, H Nishiura, M Saitoh
The 41st International ACM SIGIR Conference on Research & Development in …, 2018
Unsupervised Cross-lingual Transfer of Word Embedding Spaces
R Xu, Y Yang, N Otani, Y Wu
Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018
Knowledge embedding based graph convolutional network
D Yu, Y Yang, R Zhang, Y Wu
Proceedings of the Web Conference 2021, 1619-1628, 2021
Graph Convolutional Matrix Completion for Bipartite Edge Prediction
Y Wu, H Liu, Y Yang
International Joint Conference on Knowledge Discovery, Knowledge Engineering …, 2018
Large language models can self-improve
J Huang, SS Gu, L Hou, Y Wu, X Wang, H Yu, J Han
arXiv preprint arXiv:2210.11610, 2022
Graph-revised convolutional network
D Yu, R Zhang, Z Jiang, Y Wu, Y Yang
Joint European conference on machine learning and knowledge discovery in …, 2020
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
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 7289-7296, 2019
Cross-domain kernel induction for transfer learning
Y Wu, WC Chang, H Liu, Y Yang
Thirty-First AAAI Conference on Artificial Intelligence, 2017
Active Learning for Graph Neural Networks via Node Feature Propagation
Y Wu, Y Xu, A Singh, Y Yang, A Dubrawski
arXiv preprint arXiv:1910.07567, 2019
A deep boosting based approach for capturing the sequence binding preferences of RNA-binding proteins from high-throughput CLIP-seq data
S Li, F Dong, Y Wu, S Zhang, C Zhang, X Liu, T Jiang, J Zeng
Nucleic acids research 45 (14), e129-e129, 2017
Computational protein design using AND/OR branch-and-bound search
Y Zhou, Y Wu, J Zeng
Journal of Computational Biology 23 (6), 439-451, 2016
Token Dropping for Efficient BERT Pretraining
L Hou, RY Pang, T Zhou, Y Wu, X Song, X Song, D Zhou
Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022
Generalized multi-relational graph convolution network
D Yu, Y Yang, R Zhang, Y Wu
arXiv, 07331, 2020
Contextual Encoding for Translation Quality Estimation
J Hu, WC Chang, Y Wu, G Neubig
Proceedings of the Third Conference on Machine Translation: Shared Task …, 2018
Provable stochastic optimization for global contrastive learning: Small batch does not harm performance
Z Yuan, Y Wu, ZH Qiu, X Du, L Zhang, D Zhou, T Yang
International Conference on Machine Learning, 25760-25782, 2022
Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation
Z Wang, Y Wu, F Liu, D Liu, L Hou, H Yu, J Li, H Ji
arXiv preprint arXiv:2210.11768, 2022
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