Jiayao Zhang

According to our database, Jiayao Zhang authored at least 13 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Analysis of the ICML 2023 Ranking Data: Can Authors' Opinions of Their Own Papers Assist Peer Review in Machine Learning?

Buxin Su, Jiayao Zhang, Natalie Collina, Yuling Yan, Didong Li, Kyunghyun Cho, Jianqing Fan, Aaron Roth, Weijie J. Su

CoRR, 2024

Event Causality Identification with Synthetic Control.

Haoyu Wang, Fengze Liu, Jiayao Zhang, Dan Roth, Kyle Richardson

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Estimating the Causal Effect of Early ArXiving on Paper Acceptance.

Yanai Elazar, Jiayao Zhang, David Wadden, Bo Zhang, Noah A. Smith

Proceedings of the Causal Learning and Reasoning, 2024

2023

FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data.

Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou

Proceedings of the Eleventh International Conference on Learning Representations, 2023

COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference Perspective.

Zhaowei Wang, Quyet V. Do, Hongming Zhang, Jiayao Zhang, Weiqi Wang, Tianqing Fang, Yangqiu Song, Ginny Y. Wong, Simon See

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Investigating Fairness Disparities in Peer Review: A Language Model Enhanced Approach.

Jiayao Zhang, Hongming Zhang, Zhun Deng, Dan Roth

CoRR, 2022

Causal Inference Principles for Reasoning about Commonsense Causality.

Jiayao Zhang, Hongming Zhang, Dan Roth, Weijie J. Su

CoRR, 2022

ROCK: Causal Inference Principles for Reasoning about Commonsense Causality.

Jiayao Zhang, Hongming Zhang, Weijie J. Su, Dan Roth

Proceedings of the International Conference on Machine Learning, 2022

Some Reflections on Drawing Causal Inference using Textual Data: Parallels Between Human Subjects and Organized Texts.

Bo Zhang, Jiayao Zhang

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations.

Jiayao Zhang, Hua Wang, Weijie J. Su

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2018

Automatic Recognition of Space-Time Constellations by Learning on the Grassmann Manifold.

Yuqing Du, Guangxu Zhu, Jiayao Zhang, Kaibin Huang

IEEE Trans. Signal Process., 2018

Grassmannian Learning: Embedding Geometry Awareness in Shallow and Deep Learning.

Jiayao Zhang, Guangxu Zhu, Robert W. Heath Jr., Kaibin Huang

CoRR, 2018

Automatic Recognition of Space-Time Constellations by Learning on the Grassmann Manifold (Extended Version).

Yuqing Du, Guangxu Zhu, Jiayao Zhang, Kaibin Huang

CoRR, 2018