Cho‐Jui Hsieh - Concepedia

Author

Cho‐Jui Hsieh

University of California, Los Angeles ORCID

Also Known As

C. H. Hsieh, C. Hsieh, Cao, Lihong, Cho-Jui Hsieh, Cho‐Jui Hsieh, Eaton, Joe, Hsieh, Cho-Jui, Hsieh, Cho-jui, Li, Haoyu, Liu, Yi-Wei

458

Publications

26.4K

Citations

H-Index

186

Concepts

All Affiliations

University of California, Los Angeles The University of Texas at Austin University of California, Davis Google (United States)UCLA Health

About

Cho‐Jui Hsieh is an author at University of California, Los Angeles specializing in computer science, engineering, and machine learning.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	57	146	14.8K
2	Language Studies	12	13	2.1K
3	Business	6	6	257
4	Arts	2	2	43
5	Education	1	1	38

Cho‐Jui Hsieh

185

Publications

24.6K

Citations

H-Index

Page 1

	Year	Citations
LIBLINEAR: A Library for Large Linear Classification Rong-En Fan, Kai‐Wei Chang, Cho‐Jui Hsieh,	2008	6.6K
ZOO Pin‐Yu Chen, Huan Zhang, Yash Sharma, Artificial IntelligenceTraffic Sign IdentificationDeep Neural NetworksMachine VisionMachine Learning	2017	1.7K
VisualBERT: A Simple and Performant Baseline for Vision and Language Liunian Harold Li, Mark Yatskar, Da Yin, ArXiv.org EngineeringFlexible FrameworkPsycholinguisticsLanguage LearningPre-training Visualbert	2019	1.2K
Cluster-GCN Wei-Lin Chiang, Xuanqing Liu, Si Si,	2019	1.2K
A dual coordinate descent method for large-scale linear SVM Cho‐Jui Hsieh, Kai‐Wei Chang, Chih‐Jen Lin, Support Vector MachineSparse RepresentationEngineeringMachine LearningData Science	2008	908
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples Pin‐Yu Chen, Yash Sharma, Huan Zhang, Proceedings of the AAAI Conference on Artificial Intelligence Artificial IntelligenceConvolutional Neural NetworkDeep Neural NetworksEngineeringMachine Learning	2018	578
Training and Testing Low-degree Polynomial Data Mappings via Linear SVM Yin-Wen Chang, Cho‐Jui Hsieh, Kai‐Wei Chang, EngineeringMachine LearningNonlinear KernelsLinear SvmCorpus Linguistics	2010	478
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent Xiangru Lian, Ce Zhang, Huan Zhang, Neural Information Processing Systems Cluster ComputingEngineeringMachine LearningDistributed AlgorithmsNetwork Analysis	2017	442
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent Xiangru Lian, Ce Zhang, Huan Zhang, arXiv (Cornell University) Cluster ComputingEngineeringMachine LearningDistributed AlgorithmsNetwork Analysis	2017	406
ImageNet Training in Minutes Yang You, Zhao Zhang, Cho‐Jui Hsieh, Convolutional Neural NetworkEngineeringMachine LearningComputer ArchitectureLarge Batch Size	2018	405

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