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
1342016
Loss-aware Weight Quantization of Deep Networks
L Hou, JT Kwok
6th International Conference on Learning Representations (ICLR-2018), 2018
752018
Efficient Learning of Timeseries Shapelets
L Hou, JT Kwok, JM Zurada
the Thirtieth AAAI Conference on Artificial Intelligence, 1209-1215, 2016
572016
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
172020
Analysis of Quantized Models
L Hou, R Zhang, JT Kwok
7th International Conference on Learning Representations (ICLR-2019), 2018
162018
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
142019
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
62020
Power law in sparsified deep neural networks
L Hou, JT Kwok
arXiv preprint arXiv:1805.01891, 2018
42018
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
arXiv preprint arXiv:2012.15701, 2020
22020
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
2021
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Articles 1–10