Runtian Zhai

According to our database, Runtian Zhai authored at least 11 papers between 2019 and 2024.

Collaborative distances:

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

2024

Spectrally Transformed Kernel Regression.

Runtian Zhai, Rattana Pukdee, Roger Jin, Maria-Florina Balcan, Pradeep Ravikumar

CoRR, 2024

2023

Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation.

Runtian Zhai, Bingbin Liu, Andrej Risteski, Zico Kolter, Pradeep Ravikumar

CoRR, 2023

Predicting Out-of-Distribution Error with Confidence Optimal Transport.

Yuzhe Lu, Zhenlin Wang, Runtian Zhai, Soheil Kolouri, Joseph Campbell, Katia P. Sycara

CoRR, 2023

Characterizing Out-of-Distribution Error via Optimal Transport.

Yuzhe Lu, Yilong Qin, Runtian Zhai, Andrew Shen, Ketong Chen, Zhenlin Wang, Soheil Kolouri, Simon Stepputtis, Joseph Campbell, Katia P. Sycara

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Responsible AI (RAI) Games and Ensembles.

Yash Gupta, Runtian Zhai, Arun Sai Suggala, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding Why Generalized Reweighting Does Not Improve Over ERM.

Runtian Zhai, Chen Dan, J. Zico Kolter, Pradeep Kumar Ravikumar

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2021

Boosted CVaR Classification.

Runtian Zhai, Chen Dan, Arun Sai Suggala, J. Zico Kolter, Pradeep Ravikumar

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

DORO: Distributional and Outlier Robust Optimization.

Runtian Zhai, Chen Dan, J. Zico Kolter, Pradeep Ravikumar

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Transferred Discrepancy: Quantifying the Difference Between Representations.

Yunzhen Feng, Runtian Zhai, Di He, Liwei Wang, Bin Dong

CoRR, 2020

MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius.

Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Adversarially Robust Generalization Just Requires More Unlabeled Data.

Runtian Zhai, Tianle Cai, Di He, Chen Dan, Kun He, John E. Hopcroft, Liwei Wang

CoRR, 2019