activity
20192025
most citedDORO: Distributional and Outlier Robust Optimization

7 citations · 13 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Contextures: Representations from Contexts

Runtian Zhai, Kai Yang, Che-Ping Tsai +3

Despite the empirical success of foundation models, we do not have a systematic characterization of the representations that these models learn. In this paper, we establish the con…

cs.LG2025

Contextures: The Mechanism of Representation Learning

Runtian Zhai

This dissertation establishes the contexture theory to mathematically characterize the mechanism of representation learning, or pretraining. Despite the remarkable empirical succes…

stat.ML2024

Spectrally Transformed Kernel Regression

Runtian Zhai, Rattana Pukdee, Roger Jin +2

Unlabeled data is a key component of modern machine learning. In general, the role of unlabeled data is to impose a form of smoothness, usually from the similarity information enco…

cs.AI2023

Responsible AI (RAI) Games and Ensembles

Yash Gupta, Runtian Zhai, Arun Suggala +1

Several recent works have studied the societal effects of AI; these include issues such as fairness, robustness, and safety. In many of these objectives, a learner seeks to minimiz…

cs.LG20217 cited

DORO: Distributional and Outlier Robust Optimization

Runtian Zhai, Chen Dan, J. Zico Kolter +1

Many machine learning tasks involve subpopulation shift where the testing data distribution is a subpopulation of the training distribution. For such settings, a line of recent wor…

cs.LG20206 cited

Transferred Discrepancy: Quantifying the Difference Between Representations

Yunzhen Feng, Runtian Zhai, Di He +2

Understanding what information neural networks capture is an essential problem in deep learning, and studying whether different models capture similar features is an initial step t…