9 citations · 25 across the 8 of their papers we have counts for
8 papers
Outlier Detection Using Generative Models with Theoretical Performance Guarantees
Jirong Yi, Jingchao Gao, Tianming Wang +2
This paper considers the problem of recovering signals modeled by generative models from linear measurements contaminated with sparse outliers. We propose an outlier detection appr…
Learning Similarity between Movie Characters and Its Potential Implications on Understanding Human Experiences
Zhilin Wang, Weizhe Lin, Xiaodong Wu
While many different aspects of human experiences have been studied by the NLP community, none has captured its full richness. We propose a new task to capture this richness based…
Optimal Pooling Matrix Design for Group Testing with Dilution (Row Degree) Constraints
Jirong Yi, Myung Cho, Xiaodong Wu +2
In this paper, we consider the problem of designing optimal pooling matrix for group testing (for example, for COVID-19 virus testing) with the constraint that no more than s…
Error Correction Codes for COVID-19 Virus and Antibody Testing: Using Pooled Testing to Increase Test Reliability
Jirong Yi, Myung Cho, Xiaodong Wu +2
We consider a novel method to increase the reliability of COVID-19 virus or antibody tests by using specially designed pooled testings. Instead of testing nasal swab or blood sampl…
Do Deep Minds Think Alike? Selective Adversarial Attacks for Fine-Grained Manipulation of Multiple Deep Neural Networks
Zain Khan, Jirong Yi, Raghu Mudumbai +2
Recent works have demonstrated the existence of {\it adversarial examples} targeting a single machine learning system. In this paper we ask a simple but fundamental question of "se…
Author2Vec: A Framework for Generating User Embedding
Xiaodong Wu, Weizhe Lin, Zhilin Wang +1
Online forums and social media platforms provide noisy but valuable data every day. In this paper, we propose a novel end-to-end neural network-based user embedding system, Author2…
Trust but Verify: An Information-Theoretic Explanation for the Adversarial Fragility of Machine Learning Systems, and a General Defense against Adversarial Attacks
Jirong Yi, Hui Xie, Leixin Zhou +3
Deep-learning based classification algorithms have been shown to be susceptible to adversarial attacks: minor changes to the input of classifiers can dramatically change their outp…
Outlier Detection using Generative Models with Theoretical Performance Guarantees
Jirong Yi, Anh Duc Le, Tianming Wang +2
This paper considers the problem of recovering signals from compressed measurements contaminated with sparse outliers, which has arisen in many applications. In this paper, we prop…