activity
20182021
most citedSecure Data Sharing With Flow Model

3 citations · 4 across the 4 of their papers we have counts for

collaborators

6 papers

cs.DS20211 cited

T-SCI: A Two-Stage Conformal Inference Algorithm with Guaranteed Coverage for Cox-MLP

Jiaye Teng, Zeren Tan, Yang Yuan

It is challenging to deal with censored data, where we only have access to the incomplete information of survival time instead of its exact value. Fortunately, under linear predict…

cs.LG20203 cited

Secure Data Sharing With Flow Model

Chenwei Wu, Chenzhuang Du, Yang Yuan

In the classical multi-party computation setting, multiple parties jointly compute a function without revealing their own input data. We consider a variant of this problem, where t…

cs.LG2020

Inject Machine Learning into Significance Test for Misspecified Linear Models

Jiaye Teng, Yang Yuan

Due to its strong interpretability, linear regression is widely used in social science, from which significance test provides the significance level of models or coefficients in th…

cs.LG2020

Adversarial Data Encryption

Yingdong Hu, Liang Zhang, Wei Shan +4

In the big data era, many organizations face the dilemma of data sharing. Regular data sharing is often necessary for human-centered discussion and communication, especially in med…

cs.LG2019

Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers

Guang-He Lee, Yang Yuan, Shiyu Chang +1

Strong theoretical guarantees of robustness can be given for ensembles of classifiers generated by input randomization. Specifically, an bounded adversary cannot alter the…

cs.LG2018

An empirical study on evaluation metrics of generative adversarial networks

Qiantong Xu, Gao Huang, Yang Yuan +4

Evaluating generative adversarial networks (GANs) is inherently challenging. In this paper, we revisit several representative sample-based evaluation metrics for GANs, and address…