Jihun Hamm

According to our database, Jihun Hamm authored at least 56 papers between 2004 and 2024.

Collaborative distances:

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

2024

Marginalized Augmented Few-Shot Domain Adaptation.

Taotao Jing, Haifeng Xia, Jihun Hamm, Zhengming Ding

IEEE Trans. Neural Networks Learn. Syst., September, 2024

Enhancing Skin Disease Diagnosis: Interpretable Visual Concept Discovery with SAM Empowerment.

Xin Hu, Janet Wang, Jihun Hamm, Rie Roselyne Yotsu, Zhengming Ding

CoRR, 2024

OT-VP: Optimal Transport-guided Visual Prompting for Test-Time Adaptation.

Yunbei Zhang, Akshay Mehra, Jihun Hamm

CoRR, 2024

From Majority to Minority: A Diffusion-based Augmentation for Underrepresented Groups in Skin Lesion Analysis.

Janet Wang, Yunsung Chung, Zhengming Ding, Jihun Hamm

CoRR, 2024

Dynamic Domains, Dynamic Solutions: DPCore for Continual Test-Time Adaptation.

Yunbei Zhang, Akshay Mehra, Jihun Hamm

CoRR, 2024

On the Fly Neural Style Smoothing for Risk-Averse Domain Generalization.

Akshay Mehra, Yunbei Zhang, Bhavya Kailkhura, Jihun Hamm

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Achieving Reliable and Fair Skin Lesion Diagnosis via Unsupervised Domain Adaptation.

Janet Wang, Yunbei Zhang, Zhengming Ding, Jihun Hamm

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Test-time Assessment of a Model's Performance on Unseen Domains via Optimal Transport.

Akshay Mehra, Yunbei Zhang, Jihun Hamm

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Can Domain Adaptation Improve Accuracy and Fairness of Skin Lesion Classification?

Janet Wang, Yunbei Zhang, Zhengming Ding, Jihun Hamm

CoRR, 2023

Analysis of Task Transferability in Large Pre-trained Classifiers.

Akshay Mehra, Yunbei Zhang, Jihun Hamm

CoRR, 2023

FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation.

Yunsung Chung, Chanho Lim, Chao Huang, Nassir Marrouche, Jihun Hamm

Proceedings of the Medical Image Learning with Limited and Noisy Data, 2023

2022

Augmented Multimodality Fusion for Generalized Zero-Shot Sketch-Based Visual Retrieval.

Taotao Jing, Haifeng Xia, Jihun Hamm, Zhengming Ding

IEEE Trans. Image Process., 2022

Defeating traffic analysis via differential privacy: a case study on streaming traffic.

Xiaokuan Zhang, Jihun Hamm, Michael K. Reiter, Yinqian Zhang

Int. J. Inf. Sec., 2022

On Certifying and Improving Generalization to Unseen Domains.

Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm

CoRR, 2022

Online Evasion Attacks on Recurrent Models: The Power of Hallucinating the Future.

Byunggill Joe, Insik Shin, Jihun Hamm

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

A Spectral View of Randomized Smoothing Under Common Corruptions: Benchmarking and Improving Certified Robustness.

Jiachen Sun, Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Dan Hendrycks, Jihun Hamm, Z. Morley Mao

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Certified Adversarial Defenses Meet Out-of-Distribution Corruptions: Benchmarking Robustness and Simple Baselines.

Jiachen Sun, Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Dan Hendrycks, Jihun Hamm, Z. Morley Mao

CoRR, 2021

Machine Learning with Electronic Health Records is vulnerable to Backdoor Trigger Attacks.

Byunggill Joe, Akshay Mehra, Insik Shin, Jihun Hamm

CoRR, 2021

Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning.

Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

How Robust Are Randomized Smoothing Based Defenses to Data Poisoning?

Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Penalty Method for Inversion-Free Deep Bilevel Optimization.

Akshay Mehra, Jihun Hamm

Proceedings of the Asian Conference on Machine Learning, 2021

2020

Learning to Separate Clusters of Adversarial Representations for Robust Adversarial Detection.

Byunggill Joe, Jihun Hamm, Sung Ju Hwang, Sooel Son, Insik Shin

CoRR, 2020

2019

Statistical Privacy for Streaming Traffic.

Xiaokuan Zhang, Jihun Hamm, Michael K. Reiter, Yinqian Zhang

Proceedings of the 26th Annual Network and Distributed System Security Symposium, 2019

2018

Fluid Dynamic Models for Bhattacharyya-Based Discriminant Analysis.

Yung-Kyun Noh, Jihun Hamm, Frank Chongwoo Park, Byoung-Tak Zhang, Daniel D. Lee

IEEE Trans. Pattern Anal. Mach. Intell., 2018

K-Beam Subgradient Descent for Minimax Optimization.

Jihun Hamm, Yung-Kyun Noh

CoRR, 2018

Fast Interactive Image Retrieval using large-scale unlabeled data.

Akshay Mehra, Jihun Hamm, Mikhail Belkin

CoRR, 2018

K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning.

Jihun Hamm, Yung-Kyun Noh

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Minimax Filter: Learning to Preserve Privacy from Inference Attacks.

Jihun Hamm

J. Mach. Learn. Res., 2017

Machine vs Machine: Defending Classifiers Against Learning-based Adversarial Attacks.

Jihun Hamm

CoRR, 2017

Crowd-ML: A library for privacy-preserving machine learning on smart devices.

Jihun Hamm, Jackson Luken, Yani Xie

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Enhancing utility and privacy with noisy minimax filters.

Jihun Hamm

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016

Learning Privately from Multiparty Data.

Jihun Hamm, Paul Cao, Mikhail Belkin

CoRR, 2016

A Large-Scale Study in Predictability of Daily Activities and Places.

Gordon Euhyun Moon, Jihun Hamm

Proceedings of the 8th EAI International Conference on Mobile Computing, 2016

Learning privately from multiparty data.

Jihun Hamm, Yingjun Cao, Mikhail Belkin

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Probabilistic Zero-shot Classification with Semantic Rankings.

Jihun Hamm, Mikhail Belkin

CoRR, 2015

Qualitative Tracking Performance Evaluation without Ground-Truth.

Bohyung Han, Jihun Hamm

Proceedings of the 2015 IEEE Winter Conference on Applications of Computer Vision, 2015

Crowd-ML: A Privacy-Preserving Learning Framework for a Crowd of Smart Devices.

Jihun Hamm, Adam C. Champion, Guoxing Chen, Mikhail Belkin, Dong Xuan

Proceedings of the 35th IEEE International Conference on Distributed Computing Systems, 2015

Preserving Privacy of Continuous High-dimensional Data with Minimax Filters.

Jihun Hamm

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Regional Manifold Learning for Disease Classification.

Dong Hye Ye, Benoit Desjardins, Jihun Hamm, Harold Litt, Kilian M. Pohl

IEEE Trans. Medical Imaging, 2014

2013

FLOOR: Fusing Locally Optimal Registrations.

Dong Hye Ye, Jihun Hamm, Benoit Desjardins, Kilian M. Pohl

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013

2012

Automatic Annotation of Daily Activity from Smartphone-Based Multisensory Streams.

Jihun Hamm, Benjamin Stone, Mikhail Belkin, Simon Dennis

Proceedings of the Mobile Computing, Applications, and Services, 2012

Regional Manifold Learning for Deformable Registration of Brain MR Images.

Dong Hye Ye, Jihun Hamm, Dongjin Kwon, Christos Davatzikos, Kilian M. Pohl

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

Combining regional metrics for disease-related brain population analysis.

Dong Hye Ye, Jihun Hamm, Kilian M. Pohl

Proceedings of the 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2012

2011

Personalized video summarization with human in the loop.

Bohyung Han, Jihun Hamm, Jack Sim

Proceedings of the IEEE Workshop on Applications of Computer Vision (WACV 2011), 2011

2010

GRAM: A framework for geodesic registration on anatomical manifolds.

Jihun Hamm, Dong Hye Ye, Ragini Verma, Christos Davatzikos

Medical Image Anal., 2010

2009

Efficient Large Deformation Registration via Geodesics on a Learned Manifold of Images.

Jihun Hamm, Christos Davatzikos, Ragini Verma

Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2009

2008

Learning a Warped Subspace Model of Faces with Images of Unknown Pose and Illumination.

Jihun Ham, Daniel D. Lee

Proceedings of the VISAPP 2008: Proceedings of the Third International Conference on Computer Vision Theory and Applications, Funchal, Madeira, Portugal, January 22-25, 2008, 2008

Extended Grassmann Kernels for Subspace-Based Learning.

Jihun Ham, Daniel D. Lee

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Regularized discriminant analysis for transformation-invariant object recognition.

Yung-Kyun Noh, Jihun Ham, Daniel D. Lee

Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

Grassmann discriminant analysis: a unifying view on subspace-based learning.

Jihun Ham, Daniel D. Lee

Proceedings of the Machine Learning, 2008

2006

Learning a manifold-constrained map between image sets: applications to matching and pose estimation.

Jihun Ham, Ikkjin Ahn, Daniel D. Lee

Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 2006

Spectral Methods for Dimensionality Reduction.

Lawrence K. Saul, Kilian Q. Weinberger, Fei Sha, Jihun Ham, Daniel D. Lee

Proceedings of the Semi-Supervised Learning, 2006

2005

Cooperative relative robot localization with audible acoustic sensing.

Yuanqing Lin, Paul Vernaza, Jihun Ham, Daniel D. Lee

Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005

Learning nonlinear appearance manifolds for robot localization.

Jihun Ham, Yuanqing Lin, Daniel D. Lee

Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005

Semisupervised alignment of manifolds.

Jihun Ham, Daniel D. Lee, Lawrence K. Saul

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004

A kernel view of the dimensionality reduction of manifolds.

Jihun Ham, Daniel D. Lee, Sebastian Mika, Bernhard Schölkopf

Proceedings of the Machine Learning, 2004