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Lu Hou (侯璐)
Lu Hou (侯璐)
Noah's Ark Lab, Huawei
Verified email at huawei.com - Homepage
Title
Cited by
Cited by
Year
Loss-aware Binarization of Deep Networks
L Hou, Q Yao, JT Kwok
5th International Conference on Learning Representations (ICLR-2017), 2016
1772016
Loss-aware Weight Quantization of Deep Networks
L Hou, JT Kwok
6th International Conference on Learning Representations (ICLR-2018), 2018
1052018
Dynabert: Dynamic bert with adaptive width and depth
L Hou, Z Huang, L Shang, X Jiang, X Chen, Q Liu
Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS-2020), 2020
882020
Efficient Learning of Timeseries Shapelets
L Hou, JT Kwok, JM Zurada
the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-2016), 2016
752016
TernaryBERT: Distillation-aware Ultra-low Bit BERT
W Zhang*, L Hou*, Y Yin*, L Shang, X Chen, X Jiang, Q Liu
Conference on Empirical Methods in Natural Language Processing (EMNLP-2020), 2020
522020
BinaryBERT: Pushing the Limit of BERT Quantization
H Bai, W Zhang, L Hou, L Shang, J Jin, X Jiang, Q Liu, M Lyu, I King
59th Annual Meeting of the Association for Computational Linguistics (ACL-2021), 2021
412021
Analysis of Quantized Models
L Hou, R Zhang, JT Kwok
7th International Conference on Learning Representations (ICLR-2019), 2019
252019
Normalization Helps Training of Quantized LSTM
L Hou, J Zhu, JT Kwok, F Gao, T Qin, T Liu
Thirty-third Conference on Neural Information Processing Systems (NeurIPS-2019), 2019
212019
FILIP: Fine-grained Interactive Language-Image Pre-Training
L Yao*, R Huang*, L Hou*, G Lu, M Niu, H Xu, X Liang, Z Li, X Jiang, C Xu
10th International Conference on Learning Representations (ICLR-2022), 2022
182022
Improved OOD Generalization via Adversarial Training and Pre-training
M Yi, L Hou, J Sun, L Shang, X Jiang, Q Liu, ZM Ma
The Thirty-eighth International Conference on Machine Learning (ICML-2021), 2021
122021
Ghostbert: Generate more features with cheap operations for BERT
Z Huang, L Hou, L Shang, X Jiang, X Chen, Q Liu
59th Annual Meeting of the Association for Computational Linguistics (ACL …, 2021
102021
Reweighting Augmented Samples by Minimizing the Maximal Expected Loss
M Yi, L Hou, L Shang, X Jiang, Q Liu, ZM Ma
9th International Conference on Learning Representations (ICLR-2021), 2021
72021
Power law in sparsified deep neural networks
L Hou, JT Kwok
arXiv preprint arXiv:1805.01891, 2018
42018
Enabling Multimodal Generation on CLIP via Vision-Language Knowledge Distillation
W Dai, L Hou, L Shang, X Jiang, Q Liu, P Fung
Findings of the Association for Computational Linguistics (ACL-IJCNLP 2022), 2022
12022
Wukong: 100 Million Large-scale Chinese Cross-modal Pre-training Dataset and A Foundation Framework
J Gu, X Meng, G Lu, L Hou, M Niu, H Xu, X Liang, W Zhang, X Jiang, C Xu
arXiv preprint arXiv:2202.06767, 2022
12022
Towards efficient post-training quantization of pre-trained language models
H Bai, L Hou, L Shang, X Jiang, I King, MR Lyu
arXiv preprint arXiv:2109.15082, 2021
12021
Compression of Generative Pre-trained Language Models via Quantization
C Tao, L Hou, W Zhang, L Shang, X Jiang, Q Liu, P Luo, N Wong
60th Annual Meeting of the Association for Computational Linguistics (ACL-2022), 2022
2022
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