Rui Shu

According to our database, Rui Shu authored at least 43 papers between 2014 and 2024.

Collaborative distances:

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

2024

Learning Neural Network-Based Fault-Tolerant Formation Control for Elliptical Orbit Spacecraft.

Qingxian Jia, Rui Shu, Choon Ki Ahn, Chengxi Zhang

IEEE Trans. Aerosp. Electron. Syst., 2024

2023

Text-Enhanced Scene Image Super-Resolution via Stroke Mask and Orthogonal Attention.

Rui Shu, Cairong Zhao, Shuyang Feng, Liang Zhu, Duoqian Miao

IEEE Trans. Circuits Syst. Video Technol., November, 2023

Smooth Mask Matters: A Stroke Smoothing Text Removal Framework.

Chuyu Tu, Zhifei Zhang, Rui Shu, Shuyang Feng, Xuekuan Wang, Yuping Qiu, Cairong Zhao

Proceedings of the Pattern Recognition - 7th Asian Conference, 2023

2022

Sequential Model Optimization for Software Effort Estimation.

Tianpei Xia, Rui Shu, Xipeng Shen, Tim Menzies

IEEE Trans. Software Eng., 2022

Predicting health indicators for open source projects (using hyperparameter optimization).

Tianpei Xia, Wei Fu, Rui Shu, Rishabh Agrawal, Tim Menzies

Empir. Softw. Eng., 2022

Omni: automated ensemble with unexpected models against adversarial evasion attack.

Rui Shu, Tianpei Xia, Laurie A. Williams, Tim Menzies

Empir. Softw. Eng., 2022

Do I really need all this work to find vulnerabilities?

Sarah Elder, Nusrat Zahan, Rui Shu, Monica Metro, Valeri Kozarev, Tim Menzies, Laurie A. Williams

Empir. Softw. Eng., 2022

Do I really need all this work to find vulnerabilities? An empirical case study comparing vulnerability detection techniques on a Java application.

Sarah Elder, Nusrat Zahan, Rui Shu, Monica Metro, Valeri Kozarev, Tim Menzies, Laurie A. Williams

CoRR, 2022

Reducing the Cost of Training Security Classifier (via Optimized Semi-Supervised Learning).

Rui Shu, Tianpei Xia, Huy Tu, Laurie A. Williams, Tim Menzies

CoRR, 2022

Dazzle: Using Optimized Generative Adversarial Networks to Address Security Data Class Imbalance Issue.

Rui Shu, Tianpei Xia, Laurie A. Williams, Tim Menzies

Proceedings of the 19th IEEE/ACM International Conference on Mining Software Repositories, 2022

Bit Prioritization in Variational Autoencoders via Progressive Coding.

Rui Shu, Stefano Ermon

Proceedings of the International Conference on Machine Learning, 2022

2021

How to Better Distinguish Security Bug Reports (Using Dual Hyperparameter Optimization).

Rui Shu, Tianpei Xia, Jianfeng Chen, Laurie A. Williams, Tim Menzies

Empir. Softw. Eng., 2021

Structuring a Comprehensive Software Security Course Around the OWASP Application Security Verification Standard.

Sarah Elder, Nusrat Zahan, Valeri Kozarev, Rui Shu, Tim Menzies, Laurie A. Williams

Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering: Software Engineering Education and Training, 2021

Temporal Predictive Coding For Model-Based Planning In Latent Space.

Tung D. Nguyen, Rui Shu, Tuan Pham, Hung Bui, Stefano Ermon

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

Anytime Sampling for Autoregressive Models via Ordered Autoencoding.

Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Domain Adaptation for Human Fall Detection Using WiFi Channel State Information.

Hirokazu Narui, Rui Shu, Félix F. González-Navarro, Stefano Ermon

Proceedings of the Precision Health and Medicine - A Digital Revolution in Healthcare, 2020

Infrared Small Target Detection Based on Multiscale Local Contrast Measure Using Local Energy Factor.

Chaoqun Xia, Xiaorun Li, Liaoying Zhao, Rui Shu

IEEE Geosci. Remote. Sens. Lett., 2020

Predicting Project Health for Open Source Projects (using the DECART Hyperparameter Optimizer).

Tianpei Xia, Wei Fu, Rui Shu, Tim Menzies

CoRR, 2020

Predictive Coding for Locally-Linear Control.

Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui

Proceedings of the 37th International Conference on Machine Learning, 2020

Fair Generative Modeling via Weak Supervision.

Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon

Proceedings of the 37th International Conference on Machine Learning, 2020

Weakly Supervised Disentanglement with Guarantees.

Rui Shu, Yining Chen, Abhishek Kumar, Stefano Ermon, Ben Poole

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

Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control.

Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui

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

AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows.

Aditya Grover, Christopher Chute, Rui Shu, Zhangjie Cao, Stefano Ermon

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

A Comparison of the Acceptance of Female Subjects Between Mammography, Automated Breast Ultrasound and Hand-Held Ultrasound.

Xican Gao, Liwen Liu, Jingru Yan, Shanling Yang, Rui Shu, Yan Ju, Ge Zhang, Yao Xiao, Hongping Song

J. Medical Imaging Health Informatics, 2019

Sequential Model Optimization for Software Process Control.

Tianpei Xia, Jianfeng Chen, Rui Shu, Tim Menzies

CoRR, 2019

Improved Recognition of Security Bugs via Dual Hyperparameter Optimization.

Rui Shu, Tianpei Xia, Jianfeng Chen, Laurie A. Williams, Tim Menzies

CoRR, 2019

Fair Generative Modeling via Weak Supervision.

Aditya Grover, Kristy Choi, Rui Shu, Stefano Ermon

CoRR, 2019

Better Security Bug Report Classification via Hyperparameter Optimization.

Rui Shu, Tianpei Xia, Laurie A. Williams, Tim Menzies

CoRR, 2019

AlignFlow: Learning from multiple domains via normalizing flows.

Aditya Grover, Christopher Chute, Rui Shu, Zhangjie Cao, Stefano Ermon

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Training Variational Autoencoders with Buffered Stochastic Variational Inference.

Rui Shu, Hung H. Bui, Jay Whang, Stefano Ermon

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Generative Adversarial Examples.

Yang Song, Rui Shu, Nate Kushman, Stefano Ermon

CoRR, 2018

Bayesian optimization and attribute adjustment.

Stephan Eismann, Daniel Levy, Rui Shu, Stefan Bartzsch, Stefano Ermon

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Constructing Unrestricted Adversarial Examples with Generative Models.

Yang Song, Rui Shu, Nate Kushman, Stefano Ermon

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Amortized Inference Regularization.

Rui Shu, Hung H. Bui, Shengjia Zhao, Mykel J. Kochenderfer, Stefano Ermon

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Rethinking Style and Content Disentanglement in Variational Autoencoders.

Rui Shu, Shengjia Zhao, Mykel J. Kochenderfer

Proceedings of the 6th International Conference on Learning Representations, 2018

A DIRT-T Approach to Unsupervised Domain Adaptation.

Rui Shu, Hung H. Bui, Hirokazu Narui, Stefano Ermon

Proceedings of the 6th International Conference on Learning Representations, 2018

Robust Locally-Linear Controllable Embedding.

Ershad Banijamali, Rui Shu, Mohammad Ghavamzadeh, Hung Bui, Ali Ghodsi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Bottleneck Conditional Density Estimation.

Rui Shu, Hung Hai Bui, Mohammad Ghavamzadeh

Proceedings of the 34th International Conference on Machine Learning, 2017

A Study of Security Vulnerabilities on Docker Hub.

Rui Shu, Xiaohui Gu, William Enck

Proceedings of the Seventh ACM Conference on Data and Application Security and Privacy, 2017

2016

A Study of Security Isolation Techniques.

Rui Shu, Peipei Wang, Sigmund Albert Gorski III, Benjamin Andow, Adwait Nadkarni, Luke Deshotels, Jason Gionta, William Enck, Xiaohui Gu

ACM Comput. Surv., 2016

The Optimistic Method for Model Estimation.

James Brofos, Rui Shu, Frank Zhang

Proceedings of the Advances in Intelligent Data Analysis XV - 15th International Symposium, 2016

2015

Parallelization of Minimum Probability Flow on Binary Markov Random Fields.

James Brofos, Rui Shu

Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

2014

Automated Attribution and Intertextual Analysis.

James Brofos, Ajay Kannan, Rui Shu

CoRR, 2014