Jihun Hamm

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 43

Top Topics

Machine Learning

Differential Privacy

Interactive Image Retrieval

Top Venues

Publications

Yunbei Zhang, Akshay Mehra, Jihun Hamm
Dynamic Domains, Dynamic Solutions: DPCore for Continual Test-Time Adaptation. CoRR (2024)
Akshay Mehra, Yunbei Zhang, Jihun Hamm
Test-time Assessment of a Model's Performance on Unseen Domains via Optimal Transport. CoRR (2024)
Yunbei Zhang, Akshay Mehra, Jihun Hamm
OT-VP: Optimal Transport-guided Visual Prompting for Test-Time Adaptation. CoRR (2024)
Akshay Mehra, Yunbei Zhang, Bhavya Kailkhura, Jihun Hamm
On the Fly Neural Style Smoothing for Risk-Averse Domain Generalization. WACV (2024)
Janet Wang, Yunsung Chung, Zhengming Ding, Jihun Hamm
From Majority to Minority: A Diffusion-based Augmentation for Underrepresented Groups in Skin Lesion Analysis. CoRR (2024)
Janet Wang, Yunbei Zhang, Zhengming Ding, Jihun Hamm
Can Domain Adaptation Improve Accuracy and Fairness of Skin Lesion Classification? CoRR (2023)
Akshay Mehra, Yunbei Zhang, Bhavya Kailkhura, Jihun Hamm
On the Fly Neural Style Smoothing for Risk-Averse Domain Generalization. CoRR (2023)
Yunsung Chung, Chanho Lim, Chao Huang, Nassir Marrouche, Jihun Hamm
FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation. CoRR (2023)
Yunsung Chung, Chanho Lim, Chao Huang, Nassir Marrouche, Jihun Hamm
FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation. MILLanD@MICCAI (2023)
Akshay Mehra, Yunbei Zhang, Jihun Hamm
Analysis of Task Transferability in Large Pre-trained Classifiers. CoRR (2023)
Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm
On Certifying and Improving Generalization to Unseen Domains. CoRR (2022)
Byunggill Joe, Insik Shin, Jihun Hamm
Online Evasion Attacks on Recurrent Models: The Power of Hallucinating the Future. CoRR (2022)
Byunggill Joe, Insik Shin, Jihun Hamm
Online Evasion Attacks on Recurrent Models: The Power of Hallucinating the Future. IJCAI (2022)
Xiaokuan Zhang, Jihun Hamm, Michael K. Reiter, Yinqian Zhang
Defeating traffic analysis via differential privacy: a case study on streaming traffic. Int. J. Inf. Sec. 21 (3) (2022)
Taotao Jing, Haifeng Xia, Jihun Hamm, Zhengming Ding
Augmented Multimodality Fusion for Generalized Zero-Shot Sketch-Based Visual Retrieval. IEEE Trans. Image Process. 31 (2022)
Jiachen Sun, Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Dan Hendrycks, Jihun Hamm, Z. Morley Mao
A Spectral View of Randomized Smoothing Under Common Corruptions: Benchmarking and Improving Certified Robustness. ECCV (4) (2022)
Byunggill Joe, Akshay Mehra, Insik Shin, Jihun Hamm
Machine Learning with Electronic Health Records is vulnerable to Backdoor Trigger Attacks. CoRR (2021)
Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm
Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning. NeurIPS (2021)
Akshay Mehra, Jihun Hamm
Penalty Method for Inversion-Free Deep Bilevel Optimization. ACML (2021)
Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm
How Robust Are Randomized Smoothing Based Defenses to Data Poisoning? CVPR (2021)
Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm
Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning. CoRR (2021)
Jiachen Sun, Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Dan Hendrycks, Jihun Hamm, Z. Morley Mao
Certified Adversarial Defenses Meet Out-of-Distribution Corruptions: Benchmarking Robustness and Simple Baselines. CoRR (2021)
Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm
How Robust are Randomized Smoothing based Defenses to Data Poisoning? CoRR (2020)
Byunggill Joe, Jihun Hamm, Sung Ju Hwang, Sooel Son, Insik Shin
Learning to Separate Clusters of Adversarial Representations for Robust Adversarial Detection. CoRR (2020)
Akshay Mehra, Jihun Hamm
Penalty Method for Inversion-Free Deep Bilevel Optimization. CoRR (2019)
Xiaokuan Zhang, Jihun Hamm, Michael K. Reiter, Yinqian Zhang
Statistical Privacy for Streaming Traffic. NDSS (2019)
Jihun Hamm, Yung-Kyun Noh
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning. ICML (2018)
Akshay Mehra, Jihun Hamm, Mikhail Belkin
Fast Interactive Image Retrieval using large-scale unlabeled data. CoRR (2018)
Jihun Hamm, Yung-Kyun Noh
K-Beam Subgradient Descent for Minimax Optimization. CoRR (2018)
Yung-Kyun Noh, Jihun Hamm, Frank Chongwoo Park, Byoung-Tak Zhang, Daniel D. Lee
Fluid Dynamic Models for Bhattacharyya-Based Discriminant Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 40 (1) (2018)
Jihun Hamm, Jackson Luken, Yani Xie
Crowd-ML: A library for privacy-preserving machine learning on smart devices. ICASSP (2017)
Jihun Hamm
Enhancing utility and privacy with noisy minimax filters. ICASSP (2017)
Jihun Hamm
Minimax Filter: Learning to Preserve Privacy from Inference Attacks. J. Mach. Learn. Res. 18 (2017)
Jihun Hamm
Machine vs Machine: Defending Classifiers Against Learning-based Adversarial Attacks. CoRR (2017)
Jihun Hamm
Minimax Filter: Learning to Preserve Privacy from Inference Attacks. CoRR (2016)
Jihun Hamm, Paul Cao, Mikhail Belkin
Learning Privately from Multiparty Data. CoRR (2016)
Jihun Hamm, Yingjun Cao, Mikhail Belkin
Learning privately from multiparty data. ICML (2016)
Gordon Euhyun Moon, Jihun Hamm
A Large-Scale Study in Predictability of Daily Activities and Places. MobiCASE (2016)
Jihun Hamm
Preserving Privacy of Continuous High-dimensional Data with Minimax Filters. AISTATS (2015)
Bohyung Han, Jihun Hamm
Qualitative Tracking Performance Evaluation without Ground-Truth. WACV (2015)
Jihun Hamm, Mikhail Belkin
Probabilistic Zero-shot Classification with Semantic Rankings. CoRR (2015)
Jihun Hamm, Adam C. Champion, Guoxing Chen, Mikhail Belkin, Dong Xuan
Crowd-ML: A Privacy-Preserving Learning Framework for a Crowd of Smart Devices. CoRR (2015)
Jihun Hamm, Adam C. Champion, Guoxing Chen, Mikhail Belkin, Dong Xuan
Crowd-ML: A Privacy-Preserving Learning Framework for a Crowd of Smart Devices. ICDCS (2015)
Dong Hye Ye, Benoit Desjardins, Jihun Hamm, Harold Litt, Kilian M. Pohl
Regional Manifold Learning for Disease Classification. IEEE Trans. Medical Imaging 33 (6) (2014)
Dong Hye Ye, Jihun Hamm, Benoit Desjardins, Kilian M. Pohl
FLOOR: Fusing Locally Optimal Registrations. MICCAI (3) (2013)
Jihun Hamm, Benjamin Stone, Mikhail Belkin, Simon Dennis
Automatic Annotation of Daily Activity from Smartphone-Based Multisensory Streams. MobiCASE (2012)
Dong Hye Ye, Jihun Hamm, Dongjin Kwon, Christos Davatzikos, Kilian M. Pohl
Regional Manifold Learning for Deformable Registration of Brain MR Images. MICCAI (3) (2012)
Dong Hye Ye, Jihun Hamm, Kilian M. Pohl
Combining regional metrics for disease-related brain population analysis. ISBI (2012)
Bohyung Han, Jihun Hamm, Jack Sim
Personalized video summarization with human in the loop. WACV (2011)
Jihun Hamm, Dong Hye Ye, Ragini Verma, Christos Davatzikos
GRAM: A framework for geodesic registration on anatomical manifolds. Medical Image Anal. 14 (5) (2010)
Jihun Hamm, Christos Davatzikos, Ragini Verma
Efficient Large Deformation Registration via Geodesics on a Learned Manifold of Images. MICCAI (1) (2009)