Shiyu Chang

Assistant Professor, Ph.D.

UC Santa Barbara

chang87 [AT] ucsb.edu

Bio

Shiyu Chang is an Assistant Professor at UC Santa Barbara. His research focuses on machine learning and its applications in natural language processing and computer vision.

Most recently, he has been studying how machine predictions can be made more interpretable to humans and how human intuition and rationalization can improve AI transferability, data efficiency, and adversarial robustness.

Prior to his current position, Shiyu was a research scientist at the MIT-IBM Watson AI Lab, where he worked closely with Prof. Regina Barzilay and Prof. Tommi S. Jaakkola. He got his B.S. and Ph.D. from the University of Illinois at Urbana-Champaign. His Ph.D. advisor is Prof. Thomas S. Huang.

Students

Guanhua Zhang ( 2021 - )

Qiucheng Wu ( 2021 - )

Bairu Hou ( 2021 - )

Selected Publications

Full publications on Google Scholar.
indicates authors with equal contribution. indicates my students or interns.

Learning Stable Classifiers by Transferring Unstable Features

Yujia Bao, Shiyu Chang, Regina Barzilay

arXiv Preprint'21

Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers

Yujia Bao, Shiyu Chang, Regina Barzilay

ICML'21: International Conference on Machine Learning

Learning Stable Classifiers by Transferring Unstable Features

Yujia Bao, Shiyu Chang, Regina Barzilay

arXiv Preprint'21

Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers

Yujia Bao, Shiyu Chang, Regina Barzilay

ICML'21: International Conference on Machine Learning

The Lottery Ticket Hypothesis for Pre-trained BERT Networks

Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin

NeurIPS'20: Advances in Neural Information Processing Systems

Invariant Rationalization

Shiyu Chang, Yang Zhang, Mo Yu, Tommi S. Jaakkola

ICML'20: International Conference on Machine Learning

Unsupervised Speech Decomposition via Triple Information Bottleneck

Kaizhi Qian, Yang Zhang, Shiyu Chang, David Cox, Mark A. Hasegawa-Johnson

ICML'20: International Conference on Machine Learning

Few-shot Text Classification with Distributional Signatures

Yujia Bao☆ ‡, Menghua Wu☆ ‡, Shiyu Chang, Regina Barzilay

ICLR'20: International Conference on Learning Representations

A Game Theoretic Approach to Class-wise Selective Rationalization

Shiyu Chang, Yang Zhang, Mo Yu, Tommi S. Jaakkola

NeurIPS'19: Advances in Neural Information Processing Systems

A Stratified Approach to Robustness for Randomly Smoothed Classifiers

Guang-He Lee, Yang Yuan, Shiyu Chang, Tommi S. Jaakkola

NeurIPS'19: Advances in Neural Information Processing Systems

Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control

Mo Yu, Shiyu Chang, Yang Zhang, Tommi S. Jaakkola

EMNLP'19: Conference on Empirical Methods in Natural Language Processing

AutoVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss

Kaizhi Qian, Yang Zhang, Shiyu Chang, Xuesong Yang, Mark A. Hasegawa-Johnson

ICML'19: International Conference on Machine Learning

Deriving Machine Attention from Human Rationales

Yujia Bao, Shiyu Chang, Mo Yu, Regina Barzilay

EMNLP'18: Conference on Empirical Methods in Natural Language Processing

Image Super-Resolution via Dual-State Recurrent Networks

Wei Han☆ ‡, Shiyu Chang, Ding Liu, Mo Yu, Michael Witbrock, Thomas S. Huang

CVPR'18: IEEE Computer Vision and Pattern Recognition

Dilated Recurrent Neural Networks

Shiyu Chang, Yang Zhang, Wei Han, Mo Yu, Xiaoxiao Guo, Wei Tan, Xiaodong Cui, Michael Witbrock, Mark A. Hasegawa-Johnson, Thomas S. Huang

NIPS'17: Advances in Neural Information Processing Systems

Streaming Recommender Systems

Shiyu Chang, Yang Zhang, Jiliang Tang, Dawei Yin, Yi Chang, Mark A. Hasegawa-Johnson, Thomas S. Huang

WWW'17: ACM International World Wide Web Conference

Positive-Unlabeled Learning in Streaming Networks

Shiyu Chang, Yang Zhang, Jiliang Tang, Dawei Yin, Yi Chang, Mark A. Hasegawa-Johnson, Thomas S. Huang

KDD'16: ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Heterogeneous Network Embedding via Deep Architectures

Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang

KDD'15: ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Factorized Similarity Learning in Networks

Shiyu Chang, Guo-Jun Qi, Charu C. Aggarwal, Jiayu Zhou, Meng Wang, Thomas S. Huang

ICDM'14: IEEE International Conference on Data Mining

Learning Locally-Adaptive Decision Functions for Person Verification

Zhen Li, Shiyu Chang, Feng Liang, Thomas S. Huang, Liangliang Cao, John R. Smith

CVPR'13: IEEE Computer Vision and Pattern Recognition

Misc

- Some words keep me moving forward:

"A job well done is its own reward. You take pride in the things you do, not for others to see, not for the respect, or glory, or any other rewards it might bring. You take pride in what you do, because you're doing your best. If you believe in something, you stick with it. When things get difficult, you try harder."

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