no code implementations • 5 Feb 2024 • Yan Zhao, Zhongyun Li, Yushan Pan, Jiaxing Wang, Yihong Wang
The natural language understanding capability has always been a barrier to the intent recognition performance of the Knowledge-Based-Question-and-Answer (KBQA) system, which arises from linguistic diversity and the newly appeared intent.
no code implementations • 17 Jan 2022 • Xiaoxiao Xu, Chen Yang, Qian Yu, Zhiwei Fang, Jiaxing Wang, Chaosheng Fan, Yang He, Changping Peng, Zhangang Lin, Jingping Shao
We propose a general Variational Embedding Learning Framework (VELF) for alleviating the severe cold-start problem in CTR prediction.
1 code implementation • 16 Oct 2021 • Anda Cheng, Jiaxing Wang, Xi Sheryl Zhang, Qiang Chen, Peisong Wang, Jian Cheng
In light of this missing, we propose the very first framework that employs neural architecture search to automatic model design for private deep learning, dubbed as DPNAS.
1 code implementation • 15 Oct 2021 • Tianli Zhao, Xi Sheryl Zhang, Wentao Zhu, Jiaxing Wang, Sen yang, Ji Liu, Jian Cheng
In this paper, we present a unified framework with Joint Channel pruning and Weight pruning (JCW), and achieves a better Pareto-frontier between the latency and accuracy than previous model compression approaches.
no code implementations • 1 Sep 2021 • Tianli Zhao, Qinghao Hu, Xiangyu He, Weixiang Xu, Jiaxing Wang, Cong Leng, Jian Cheng
Acceleration of deep neural networks to meet a specific latency constraint is essential for their deployment on mobile devices.
1 code implementation • NeurIPS 2020 • Jiaxing Wang, Haoli Bai, Jiaxiang Wu, Xupeng Shi, Junzhou Huang, Irwin King, Michael Lyu, Jian Cheng
Nevertheless, it is unclear how parameter sharing affects the searching process.
no code implementations • 25 May 2019 • Jiaxing Wang, Yin Zheng, Xiaoshuang Chen, Junzhou Huang, Jian Cheng
Semi-supervised learning (SSL) provides a powerful framework for leveraging unlabeled data when labels are limited or expensive to obtain.
1 code implementation • 18 May 2019 • Xiaoshuang Chen, Yin Zheng, Jiaxing Wang, Wenye Ma, Junzhou Huang
Factorization machines (FM) are a popular model class to learn pairwise interactions by a low-rank approximation.
no code implementations • 20 Mar 2018 • Jiaxing Wang, Jihua Zhu, Shanmin Pang, Zhongyu Li, Yaochen Li, Xueming Qian
Aggregating deep convolutional features into a global image vector has attracted sustained attention in image retrieval.