Shang-Tse Chen

According to our database, Shang-Tse Chen authored at least 31 papers between 2009 and 2024.

Collaborative distances:

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

2024

Towards Large Certified Radius in Randomized Smoothing Using Quasiconcave Optimization.

Bo-Han Kung, Shang-Tse Chen

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Step by Step to Fairness: Attributing Societal Bias in Task-oriented Dialogue Systems.

Hsuan Su, Rebecca Qian, Chinnadhurai Sankar, Shahin Shayandeh, Shang-Tse Chen, Hung-yi Lee, Daniel M. Bikel

CoRR, 2023

Learning from Red Teaming: Gender Bias Provocation and Mitigation in Large Language Models.

Hsuan Su, Cheng-Chu Cheng, Hua Farn, Shachi H. Kumar, Saurav Sahay, Shang-Tse Chen, Hung-yi Lee

CoRR, 2023

Annealing Self-Distillation Rectification Improves Adversarial Training.

Yu-Yu Wu, Hung-Jui Wang, Shang-Tse Chen

CoRR, 2023

Position Matters! Empirical Study of Order Effect in Knowledge-grounded Dialogue.

Hsuan Su, Shachi H. Kumar, Sahisnu Mazumder, Wenda Chen, Ramesh Manuvinakurike, Eda Okur, Saurav Sahay, Lama Nachman, Shang-Tse Chen, Hung-yi Lee

CoRR, 2023

QCRS: Improve Randomized Smoothing using Quasi-Concave Optimization.

Bo-Han Kung, Shang-Tse Chen

CoRR, 2023

Fair Robust Active Learning by Joint Inconsistency.

Tsung-Han Wu, Hung-Ting Su, Shang-Tse Chen, Winston H. Hsu

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Fair Robust Active Learning by Joint Inconsistency.

Tsung-Han Wu, Shang-Tse Chen, Winston H. Hsu

CoRR, 2022

Enhancing Targeted Attack Transferability via Diversified Weight Pruning.

Hung-Jui Wang, Yu-Yu Wu, Shang-Tse Chen

CoRR, 2022

Few-shot Prompting Towards Controllable Response Generation.

Hsuan Su, Po-Han Chi, Shih-Cheng Huang, Ho-Lam Chung, Saurav Sahay, Shang-Tse Chen, Hung-Yi Lee

CoRR, 2022

2020

AI-infused Security: Robust Defense by Bridging Theory and Practice.

Shang-Tse Chen

PhD thesis, 2020

UnMask: Adversarial Detection and Defense Through Robust Feature Alignment.

Scott Freitas, Shang-Tse Chen, Zijie J. Wang, Duen Horng Chau

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Talk Proposal: Towards the Realistic Evaluation of Evasion Attacks using CARLA.

Cory Cornelius, Shang-Tse Chen, Jason Martin, Duen Horng Chau

CoRR, 2019

2018

Chronodes: Interactive Multifocus Exploration of Event Sequences.

Peter J. Polack Jr., Shang-Tse Chen, Minsuk Kahng, Kaya de Barbaro, Rahul C. Basole, Moushumi Sharmin, Duen Horng Chau

ACM Trans. Interact. Intell. Syst., 2018

Robust Physical Adversarial Attack on Faster R-CNN Object Detector.

Shang-Tse Chen, Cory Cornelius, Jason Martin, Duen Horng Chau

CoRR, 2018

ADAGIO: Interactive Experimentation with Adversarial Attack and Defense for Audio.

Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Li Chen, Michael E. Kounavis, Duen Horng Chau

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector.

Shang-Tse Chen, Cory Cornelius, Jason Martin, Duen Horng (Polo) Chau

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

SHIELD: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression.

Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Siwei Li, Li Chen, Michael E. Kounavis, Duen Horng Chau

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Diversified Strategies for Mitigating Adversarial Attacks in Multiagent Systems.

Maria-Florina Balcan, Avrim Blum, Shang-Tse Chen

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017

Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression.

Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Li Chen, Michael E. Kounavis, Duen Horng Chau

CoRR, 2017

Predicting Cyber Threats with Virtual Security Products.

Shang-Tse Chen, Yufei Han, Duen Horng Chau, Christopher S. Gates, Michael Hart, Kevin A. Roundy

Proceedings of the 33rd Annual Computer Security Applications Conference, 2017

Exploratory Visual Analytics of Mobile Health Data: Sensemaking Challenges and Opportunities.

Peter J. Polack Jr., Moushumi Sharmin, Kaya de Barbaro, Minsuk Kahng, Shang-Tse Chen, Duen Horng Chau

Proceedings of the Mobile Health - Sensors, Analytic Methods, and Applications, 2017

2016

Chronodes: Interactive Multi-focus Exploration of Event Sequences.

Peter J. Polack Jr., Shang-Tse Chen, Minsuk Kahng, Kaya de Barbaro, Moushumi Sharmin, Rahul C. Basole, Duen Horng Chau

CoRR, 2016

Firebird: Predicting Fire Risk and Prioritizing Fire Inspections in Atlanta.

Michael A. Madaio, Shang-Tse Chen, Oliver L. Haimson, Wenwen Zhang, Xiang Cheng, Matthew Hinds-Aldrich, Duen Horng Chau, Bistra Dilkina

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Communication Efficient Distributed Agnostic Boosting.

Shang-Tse Chen, Maria-Florina Balcan, Duen Horng Chau

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Spotting Suspicious Reviews via (Quasi-)clique Extraction.

Paras Jain, Shang-Tse Chen, Mozhgan Azimpourkivi, Duen Horng Chau, Bogdan Carbunar

CoRR, 2015

Benchmarking renderscript: potential for energy efficient multi-core mobile devices.

Qianao Ju, Shang-Tse Chen, Ying Zhang

Proceedings of the 12th Annual IEEE International Conference on Sensing, 2015

TimeStitch: Interactive multi-focus cohort discovery and comparison.

Peter J. Polack Jr., Shang-Tse Chen, Minsuk Kahng, Moushumi Sharmin, Duen Horng Chau

Proceedings of the 10th IEEE Conference on Visual Analytics Science and Technology, 2015

2014

Boosting with Online Binary Learners for the Multiclass Bandit Problem.

Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu

Proceedings of the 31th International Conference on Machine Learning, 2014

2012

An Online Boosting Algorithm with Theoretical Justifications.

Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu

Proceedings of the 29th International Conference on Machine Learning, 2012

2009

An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes.

Hung-Yi Lo, Kai-Wei Chang, Shang-Tse Chen, Tsung-Hsien Chiang, Chun-Sung Ferng, Cho-Jui Hsieh, Yi-Kuang Ko, Tsung-Ting Kuo, Hung-Che Lai, Ken-Yi Lin, Chia-Hsuan Wang, Hsiang-Fu Yu, Chih-Jen Lin, Hsuan-Tien Lin, Shou-De Lin

Proceedings of KDD-Cup 2009 competition, Paris, France, June 28, 2009, 2009