no code implementations • 18 Oct 2022 • Yong Wu, Shekhor Chanda, Mehrdad Hosseinzadeh, Zhi Liu, Yang Wang
In this paper, we propose task-specific meta distillation that simultaneously learns two models in meta-learning: a large teacher model and a small student model.
2 code implementations • 6 Mar 2021 • Shabnam Daghaghi, Nicholas Meisburger, Mengnan Zhao, Yong Wu, Sameh Gobriel, Charlie Tai, Anshumali Shrivastava
Our work highlights several novel perspectives and opportunities for implementing randomized algorithms for deep learning on modern CPUs.
1 code implementation • 22 Jan 2021 • Gongyang Li, Zhi Liu, Ran Shi, Zheng Hu, Weijie Wei, Yong Wu, Mengke Huang, Haibin Ling
In this paper, we focus on Personal Fixations-based Object Segmentation (PFOS) to address issues in previous studies, such as the lack of appropriate dataset and the ambiguity in fixations-based interaction.
no code implementations • 4 Jun 2020 • Haichen Shen, Jared Roesch, Zhi Chen, Wei Chen, Yong Wu, Mu Li, Vin Sharma, Zachary Tatlock, Yida Wang
Modern deep neural networks increasingly make use of features such as dynamic control flow, data structures and dynamic tensor shapes.
no code implementations • 23 Nov 2019 • Di Wu, Chao Wang, Yong Wu, De-Shuang Huang
Besides, most of the multi-scale models embedding the multi-scale feature learning block into the feature extraction deep network, which reduces the efficiency of inference network.
1 code implementation • 11 Apr 2016 • Xundong Wu, Yong Wu, Yong Zhao
We trained Binarized Neural Networks (BNNs) on the high resolution ImageNet ILSVRC-2102 dataset classification task and achieved a good performance.