Ching-Yun Ko

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 24

Top Topics

Component Analysis

Contrastive Divergence

Top Venues

Publications

Yanwei Wang, Ching-Yun Ko, Pulkit Agrawal
Visual Pre-Training for Navigation: What Can We Learn from Noise? IROS (2023)
Peiqi Wang, Yingcheng Liu, Ching-Yun Ko, William M. Wells III, Seth J. Berkowitz, Steven Horng, Polina Golland
Sample-Specific Debiasing for Better Image-Text Models. CoRR (2023)
Peiqi Wang, Yingcheng Liu, Ching-Yun Ko, William M. Wells III, Seth J. Berkowitz, Steven Horng, Polina Golland
Sample-Specific Debiasing for Better Image-Text Models. MLHC (2023)
Wei Liao, Ching-Yun Ko, Tsui-Wei Weng, Luca Daniel, Joel Voldman
Facile Prediction of Neutrophil Activation State from Microscopy Images: A New Dataset and Comparative Deep Learning Approaches. ISBI (2022)
Yanwei Wang, Ching-Yun Ko
Visual Pre-training for Navigation: What Can We Learn from Noise? CoRR (2022)
Ching-Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng
Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework. ICML (2022)
Ching-Yun Ko, Pin-Yu Chen, Jeet Mohapatra, Payel Das, Luca Daniel
SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data. CoRR (2022)
Jeet Mohapatra, Ching-Yun Ko, Lily Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Hidden Cost of Randomized Smoothing. AISTATS (2021)
Ching-Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng
Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework. CoRR (2021)
Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Higher-Order Certification for Randomized Smoothing. CoRR (2020)
Ching-Yun Ko, Kim Batselier, Luca Daniel, Wenjian Yu, Ngai Wong
Fast and Accurate Tensor Completion With Total Variation Regularized Tensor Trains. IEEE Trans. Image Process. 29 (2020)
Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Sijia Liu, Pin-Yu Chen, Luca Daniel
Rethinking Randomized Smoothing for Adversarial Robustness. CoRR (2020)
Zhaoyang Lyu, Ching-Yun Ko, Zhifeng Kong, Ngai Wong, Dahua Lin, Luca Daniel
Fastened CROWN: Tightened Neural Network Robustness Certificates. AAAI (2020)
Rui Lin, Ching-Yun Ko, Zhuolun He, Cong Chen, Yuan Cheng, Hao Yu, Graziano Chesi, Ngai Wong
HOTCAKE: Higher Order Tucker Articulated Kernels for Deeper CNN Compression. CoRR (2020)
Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Higher-Order Certification For Randomized Smoothing. NeurIPS (2020)
Ching-Yun Ko, Cong Chen, Zhuolun He, Yuke Zhang, Kim Batselier, Ngai Wong
Deep Model Compression and Inference Speedup of Sum-Product Networks on Tensor Trains. IEEE Trans. Neural Networks Learn. Syst. 31 (7) (2020)
Ching-Yun Ko, Zhaoyang Lyu, Tsui-Wei Weng, Luca Daniel, Ngai Wong, Dahua Lin
POPQORN: Quantifying Robustness of Recurrent Neural Networks. CoRR (2019)
Ching-Yun Ko, Zhaoyang Lyu, Lily Weng, Luca Daniel, Ngai Wong, Dahua Lin
POPQORN: Quantifying Robustness of Recurrent Neural Networks. ICML (2019)
Cong Chen, Kim Batselier, Ching-Yun Ko, Ngai Wong
Matrix Product Operator Restricted Boltzmann Machines. IJCNN (2019)
Ching-Yun Ko, Rui Lin, Shu Li, Ngai Wong
MiSC: Mixed Strategies Crowdsourcing. CoRR (2019)
Kim Batselier, Ching-Yun Ko, Ngai Wong
Extended Kalman Filtering with Low-Rank Tensor Networks for MIMO Volterra System Identification. CDC (2019)
Zhaoyang Lyu, Ching-Yun Ko, Zhifeng Kong, Ngai Wong, Dahua Lin, Luca Daniel
Fastened CROWN: Tightened Neural Network Robustness Certificates. CoRR (2019)
Cong Chen, Kim Batselier, Ching-Yun Ko, Ngai Wong
A Support Tensor Train Machine. IJCNN (2019)
Cong Chen, Kim Batselier, Ching-Yun Ko, Ngai Wong
Matrix Product Operator Restricted Boltzmann Machines. CoRR (2018)