1 code implementation • NeurIPS 2020 • Yuanbiao Gou, Boyun Li, Zitao Liu, Songfan Yang, Xi Peng
Different from the existing labor-intensive handcrafted architecture design paradigms, we present a novel method, termed as multi-sCaLe nEural ARchitecture sEarch for image Restoration (CLEARER), which is a specifically designed neural architecture search (NAS) for image restoration.
no code implementations • 16 May 2020 • Gale Yan Huang, Jiahao Chen, Haochen Liu, Weiping Fu, Wenbiao Ding, Jiliang Tang, Songfan Yang, Guoliang Li, Zitao Liu
Asking questions is one of the most crucial pedagogical techniques used by teachers in class.
no code implementations • 21 Apr 2020 • Pengcheng Wang, ZiHao Wang, Zhilong Ji, Xiao Liu, Songfan Yang, Zhongqin Wu
This paper introduces our approach to the EmotioNet Challenge 2020.
2 code implementations • 22 Nov 2019 • Zhiwei Wang, Hui Liu, Jiliang Tang, Songfan Yang, Gale Yan Huang, Zitao Liu
Robust language processing systems are becoming increasingly important given the recent awareness of dangerous situations where brittle machine learning models can be easily broken with the presence of noises.
no code implementations • 22 Oct 2019 • Hang Li, Yu Kang, Wenbiao Ding, Song Yang, Songfan Yang, Gale Yan Huang, Zitao Liu
The experimental results demonstrate the benefits of our approach on learning attention based neural network from classroom data with different modalities, and show our approach is able to outperform state-of-the-art baselines in terms of various evaluation metrics.
no code implementations • 1 Aug 2019 • Wenbiao Ding, Guowei Xu, Tianqiao Liu, Weiping Fu, Yujia Song, Chaoyou Guo, Cong Kong, Songfan Yang, Gale Yan Huang, Zitao Liu
In our offline experiments, we show that Dolphin improves both phonological fluency and semantic relevance evaluation performance when compared to state-of-the-art baselines on real-world educational data sets.
1 code implementation • 18 Jul 2019 • Guowei Xu, Wenbiao Ding, Jiliang Tang, Songfan Yang, Gale Yan Huang, Zitao Liu
In practice, the crowdsourced labels are usually inconsistent among crowd workers given their diverse expertise and the number of crowdsourced labels is very limited.
1 code implementation • 18 Jul 2019 • Tianqiao Liu, Zhiwei Wang, Jiliang Tang, Songfan Yang, Gale Yan Huang, Zitao Liu
In modern recommender systems, both users and items are associated with rich side information, which can help understand users and items.
no code implementations • ICCV 2015 • Songfan Yang, Deva Ramanan
We explore multi-scale convolutional neural nets (CNNs) for image classification.