Haw-Shiuan Chang
Haw-Shiuan Chang
School of Computer Science, UMass, Amherst
Verified email at cs.umass.edu - Homepage
Title
Cited by
Cited by
Year
Active bias: Training more accurate neural networks by emphasizing high variance samples
HS Chang, E Learned-Miller, A McCallum
arXiv preprint arXiv:1704.07433, 2017
1282017
Exploring visual and motion saliency for automatic video object extraction
WT Li, HS Chang, KC Lien, HT Chang, YCF Wang
IEEE transactions on image processing 22 (7), 2600-2610, 2013
692013
Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection
HS Chang, ZY Wang, L Vilnis, A McCallum
Proceedings of the 2018 Conference of the North American Chapter of the …, 2018
45*2018
The materials science procedural text corpus: Annotating materials synthesis procedures with shallow semantic structures
S Mysore, Z Jensen, E Kim, K Huang, HS Chang, E Strubell, J Flanigan, ...
arXiv preprint arXiv:1905.06939, 2019
252019
Inorganic materials synthesis planning with literature-trained neural networks
E Kim, Z Jensen, A van Grootel, K Huang, M Staib, S Mysore, HS Chang, ...
Journal of chemical information and modeling 60 (3), 1194-1201, 2020
222020
Optimizing the decomposition for multiple foreground cosegmentation
HS Chang, YCF Wang
Computer Vision and Image Understanding 141, 18-27, 2015
192015
Automatically extracting action graphs from materials science synthesis procedures
S Mysore, E Kim, E Strubell, A Liu, HS Chang, S Kompella, K Huang, ...
arXiv preprint arXiv:1711.06872, 2017
182017
Active learning for crowdsourced QoE modeling
HS Chang, CF Hsu, T Hoßfeld, KT Chen
IEEE Transactions on Multimedia 20 (12), 3337-3352, 2018
122018
Modeling Exercise Relationships in E-Learning: A Unified Approach
HS Chang, HJ Hsu, KT Chen
International Conference on Educational Data Mining (EDM), 2015
122015
Superpixel-based large displacement optical flow
HS Chang, YCF Wang
2013 IEEE International Conference on Image Processing, 3835-3839, 2013
102013
Extracting Multilingual Relations under Limited Resources: TAC 2016 Cold-Start KB construction and Slot-Filling using Compositional Universal Schema.
HS Chang, A Munir, A Liu, JTZ Wei, A Traylor, A Nagesh, N Monath, ...
TAC, 2016
92016
Efficient graph-based word sense induction by distributional inclusion vector embeddings
HS Chang, A Agrawal, A Ganesh, A Desai, V Mathur, A Hough, ...
arXiv preprint arXiv:1804.03257, 2018
62018
AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types
XL Dong, X He, A Kan, X Li, Y Liang, J Ma, YE Xu, C Zhang, T Zhao, ...
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
42020
Extending multi-sense word embedding to phrases and sentences for unsupervised semantic applications
HS Chang, A Agrawal, A McCallum
arXiv preprint arXiv:2103.15330, 2021
22021
Changing the Mind of Transformers for Topically-Controllable Language Generation
HS Chang, J Yuan, M Iyyer, A McCallum
arXiv preprint arXiv:2103.15335, 2021
12021
Multi-facet Universal Schema
R Paul, HS Chang, A McCallum
arXiv preprint arXiv:2103.15339, 2021
12021
Overcoming Practical Issues of Deep Active Learning and its Applications on Named Entity Recognition.
HS Chang, S Vembu, S Mohan, R Uppaal, A McCallum
12019
Using error decay prediction to overcome practical issues of deep active learning for named entity recognition
HS Chang, S Vembu, S Mohan, R Uppaal, A McCallum
Machine Learning 109 (9), 1749-1778, 2020
2020
AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types
X Luna Dong, X He, A Kan, X Li, Y Liang, J Ma, YE Xu, C Zhang, T Zhao, ...
arXiv e-prints, arXiv: 2006.13473, 2020
2020
Learning Multi-facet Embeddings of Phrases and Sentences using Sparse Coding for Unsupervised Semantic Applications
HS Chang, A Agrawal, A McCallum
2019
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Articles 1–20