20 citations · 44 across the 10 of their papers we have counts for
9 papers
Neural Multi-Task Learning for Teacher Question Detection in Online Classrooms
Gale Yan Huang, Jiahao Chen, Haochen Liu +6
Asking questions is one of the most crucial pedagogical techniques used by teachers in class. It not only offers open-ended discussions between teachers and students to exchange id…
TAL EmotioNet Challenge 2020 Rethinking the Model Chosen Problem in Multi-Task Learning
Pengcheng Wang, Zihao Wang, Zhilong Ji +3
This paper introduces our approach to the EmotioNet Challenge 2020. We pose the AU recognition problem as a multi-task learning problem, where the non-rigid facial muscle motion (m…
Identifying At-Risk K-12 Students in Multimodal Online Environments: A Machine Learning Approach
Hang Li, Wenbiao Ding, Zitao Liu
With the rapid emergence of K-12 online learning platforms, a new era of education has been opened up. It is crucial to have a dropout warning framework to preemptively identify K-…
Learning Multi-level Dependencies for Robust Word Recognition
Zhiwei Wang, Hui Liu, Jiliang Tang +3
Robust language processing systems are becoming increasingly important given the recent awareness of dangerous situations where brittle machine learning models can be easily broken…
Multimodal Learning For Classroom Activity Detection
Hang Li, Yu Kang, Wenbiao Ding +4
Classroom activity detection (CAD) focuses on accurately classifying whether the teacher or student is speaking and recording both the length of individual utterances during a clas…
Dolphin: A Spoken Language Proficiency Assessment System for Elementary Education
Wenbiao Ding, Guowei Xu, Tianqiao Liu +7
Spoken language proficiency is critically important for children's growth and personal development. Due to the limited and imbalanced educational resources in China, elementary stu…
Learning Effective Embeddings From Crowdsourced Labels: An Educational Case Study
Guowei Xu, Wenbiao Ding, Jiliang Tang +3
Learning representation has been proven to be helpful in numerous machine learning tasks. The success of the majority of existing representation learning approaches often requires…
Recommender Systems with Heterogeneous Side Information
Tianqiao Liu, Zhiwei Wang, Jiliang Tang +3
In modern recommender systems, both users and items are associated with rich side information, which can help understand users and items. Such information is typically heterogeneou…
Multi-scale recognition with DAG-CNNs
Songfan Yang, Deva Ramanan
We explore multi-scale convolutional neural nets (CNNs) for image classification. Contemporary approaches extract features from a single output layer. By extracting features from m…