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ORCIDKa-Ho Chow 0001
Ka Ho Chow 0001
Person information
- affiliation: University of Hong Kong, School of Computing and Data Science, Hong Kong
- affiliation (PhD 2023): Georgia Institute of Technology, School of Computer Science, Atlanta, GA, USA
- affiliation (former): Hong Kong University of Science and Technology, Department of Computer Science and Engineering, Hong Kong
Other persons with the same name
- Ka-Ho Chow (aka: Ka Ho Chow) — disambiguation page
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2020 – today
- 2026
[i34]Haoyang Hu, Zhejun Jiang, Yueming Lyu, Junyuan Zhang, Yi Liu, Ka-Ho Chow
:
Confundo: Learning to Generate Robust Poison for Practical RAG Systems. CoRR abs/2602.06616 (2026)- 2025
- [c36]Kerui Wu, Ka-Ho Chow, Wenqi Wei, Lei Yu:
On the Adversarial Robustness of Graph Neural Networks with Graph Reduction. ESORICS (1) 2025: 388-409 - [c35]Kaijing Luo, Ka-Ho Chow:
Harmless Backdoor-based Client-side Watermarking in Federated Learning. EuroS&P 2025: 1002-1020 - [c34]Junjie Shan, Ziqi Zhao, Jialin Lu, Rui Zhang, Siu Ming Yiu, Ka-Ho Chow:
Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning. ICCV 2025: 1-10 - [c33]Junyuan Zhang, Qintong Zhang, Bin Wang, Linke Ouyang, Zichen Wen, Ying Li, Ka-Ho Chow, Conghui He, Wentao Zhang:
OCR Hinders RAG: Evaluating the Cascading Impact of OCR on Retrieval-Augmented Generation. ICCV 2025: 17443-17453 - [i33]Yinuo Wang, Juhyun Bae, Ka Ho Chow, Shenyang Chen, Shreyash Gupta:
Deep-Learning-Assisted Highly-Accurate COVID-19 Diagnosis on Lung Computed Tomography Images. CoRR abs/2507.04252 (2025) - [i32]Ziling Wang, Shuya Yang, Jialin Lu, Ka-Ho Chow:
Protego: User-Centric Pose-Invariant Privacy Protection Against Face Recognition-Induced Digital Footprint Exposure. CoRR abs/2508.02034 (2025) - [i31]Junyuan Zhang, Bin Wang, Qintong Zhang, Fan Wu, Zichen Wen, Jialin Lu, Junjie Shan, Ziqi Zhao, Shuya Yang, Ziling Wang, Ziyang Miao, Huaping Zhong, Yuhang Zang, Xiaoyi Dong, Ka-Ho Chow, Conghui He:
TRivia: Self-supervised Fine-tuning of Vision-Language Models for Table Recognition. CoRR abs/2512.01248 (2025) - [i30]Qintong Zhang, Junyuan Zhang, Zhifei Ren, Linke Ouyang, Zichen Wen, Junbo Niu, Yuan Qu, Bin Wang, Ka-Ho Chow, Conghui He, Wentao Zhang:
DOCR-Inspector: Fine-Grained and Automated Evaluation of Document Parsing with VLM. CoRR abs/2512.10619 (2025) - 2024
- [b1]Ka-Ho Chow:
Robust Learning Frameworks and Algorithms for Scalable Data Systems. Georgia Institute of Technology, Atlanta, GA, USA, 2024 - [j7]Ka-Ho Chow, Sihao Hu, Tiansheng Huang, Fatih Ilhan, Wenqi Wei, Ling Liu:
Diversity-driven Privacy Protection Masks Against Unauthorized Face Recognition. Proc. Priv. Enhancing Technol. 2024(4): 381-392 (2024) - [j6]Yanzhao Wu, Ka-Ho Chow, Wenqi Wei, Ling Liu:
Hierarchical Pruning of Deep Ensembles with Focal Diversity. ACM Trans. Intell. Syst. Technol. 15(1): 15:1-15:24 (2024) - [j5]Wenqi Wei, Ka-Ho Chow, Yanzhao Wu, Ling Liu:
Demystifying Data Poisoning Attacks in Distributed Learning as a Service. IEEE Trans. Serv. Comput. 17(1): 237-250 (2024) - [c32]Yuxuan Zhu, Michael Mandulak, Kerui Wu, George M. Slota, Yuseok Jeon, Ka-Ho Chow, Lei Yu:
On the Robustness of Graph Reduction Against GNN Backdoor. AISec@CCS 2024: 65-76 - [c31]Nawrin Tabassum, Ka-Ho Chow, Xuyu Wang, Wenbin Zhang, Yanzhao Wu:
On the Efficiency of Privacy Attacks in Federated Learning. CVPR Workshops 2024: 4226-4235 - [c30]Ka-Ho Chow, Sihao Hu, Tiansheng Huang, Ling Liu:
Personalized Privacy Protection Mask Against Unauthorized Facial Recognition. ECCV (82) 2024: 434-450 - [c29]Ka-Ho Chow, Umesh Deshpande, Veera Deenadhayalan, Sangeetha Seshadri, Ling Liu:
Atlas: Hybrid Cloud Migration Advisor for Interactive Microservices. EuroSys 2024: 870-887 - [c28]Xueqing Zhang, Junkai Zhang, Ka-Ho Chow, Juntao Chen, Ying Mao, Mohamed Rahouti, Xiang Li, Yuchen Liu, Wenqi Wei:
Demo: Visualizing the Shadows: Unveiling Data Poisoning Behaviors in Federated Learning. ICDCS 2024: 1431-1434 - [c27]Fatih Ilhan, Ka-Ho Chow, Sihao Hu, Tiansheng Huang, Selim F. Tekin, Wenqi Wei, Yanzhao Wu, Myungjin Lee, Ramana Kompella, Hugo Latapie, Gaowen Liu, Ling Liu:
Adaptive Deep Neural Network Inference Optimization with EENet. WACV 2024: 1362-1371 - [c26]Sihao Hu, Tiansheng Huang, Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, Ling Liu:
ZipZap: Efficient Training of Language Models for Large-Scale Fraud Detection on Blockchain. WWW 2024: 2807-2816 - [i29]Ka-Ho Chow, Wenqi Wei, Lei Yu:
Imperio: Language-Guided Backdoor Attacks for Arbitrary Model Control. CoRR abs/2401.01085 (2024) - [i28]Lei Yu, Meng Han, Yiming Li, Changting Lin, Yao Zhang, Mingyang Zhang, Yan Liu, Haiqin Weng, Yuseok Jeon, Ka-Ho Chow, Stacy Patterson:
A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective. CoRR abs/2402.03688 (2024) - [i27]Selim Furkan Tekin, Fatih Ilhan, Tiansheng Huang, Sihao Hu, Ka-Ho Chow, Margaret L. Loper, Ling Liu:
Robust Few-Shot Ensemble Learning with Focal Diversity-Based Pruning. CoRR abs/2404.04434 (2024) - [i26]Nawrin Tabassum, Ka-Ho Chow, Xuyu Wang, Wenbin Zhang, Yanzhao Wu:
On the Efficiency of Privacy Attacks in Federated Learning. CoRR abs/2404.09430 (2024) - [i25]Xueqing Zhang, Junkai Zhang, Ka-Ho Chow, Juntao Chen, Ying Mao, Mohamed Rahouti, Xiang Li, Yuchen Liu, Wenqi Wei:
Visualizing the Shadows: Unveiling Data Poisoning Behaviors in Federated Learning. CoRR abs/2405.16707 (2024) - [i24]Yuxuan Zhu, Michael Mandulak, Kerui Wu, George M. Slota, Yuseok Jeon, Ka-Ho Chow, Lei Yu:
On the Robustness of Graph Reduction Against GNN Backdoor. CoRR abs/2407.02431 (2024) - [i23]Ka-Ho Chow, Sihao Hu, Tiansheng Huang, Ling Liu:
Personalized Privacy Protection Mask Against Unauthorized Facial Recognition. CoRR abs/2407.13975 (2024) - [i22]Kaijing Luo, Ka-Ho Chow:
Unharmful Backdoor-based Client-side Watermarking in Federated Learning. CoRR abs/2410.21179 (2024) - [i21]Jialin Lu, Junjie Shan, Ziqi Zhao, Ka-Ho Chow:
AnywhereDoor: Multi-Target Backdoor Attacks on Object Detection. CoRR abs/2411.14243 (2024) - [i20]Junjie Shan, Ziqi Zhao, Jialin Lu, Rui Zhang, Siu Ming Yiu, Ka-Ho Chow:
Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning. CoRR abs/2411.14937 (2024) - [i19]Junyuan Zhang, Qintong Zhang, Bin Wang, Linke Ouyang, Zichen Wen, Ying Li, Ka-Ho Chow, Conghui He, Wentao Zhang:
OCR Hinders RAG: Evaluating the Cascading Impact of OCR on Retrieval-Augmented Generation. CoRR abs/2412.02592 (2024) - [i18]Kerui Wu, Ka-Ho Chow, Wenqi Wei, Lei Yu:
Understanding the Impact of Graph Reduction on Adversarial Robustness in Graph Neural Networks. CoRR abs/2412.05883 (2024) - [i17]Rui Zhang, Ka-Ho Chow, Ping Li:
Building Gradient Bridges: Label Leakage from Restricted Gradient Sharing in Federated Learning. CoRR abs/2412.12640 (2024) - 2023
- [j4]Jiajie Tan, Hang Wu, Ka Ho Chow, S.-H. Gary Chan:
Implicit Multimodal Crowdsourcing for Joint RF and Geomagnetic Fingerprinting. IEEE Trans. Mob. Comput. 22(2): 935-950 (2023) - [j3]Wenqi Wei, Ling Liu, Jingya Zhou, Ka-Ho Chow, Yanzhao Wu:
Securing Distributed SGD Against Gradient Leakage Threats. IEEE Trans. Parallel Distributed Syst. 34(7): 2040-2054 (2023) - [c25]Ka-Ho Chow, Ling Liu, Wenqi Wei, Fatih Ilhan, Yanzhao Wu:
STDLens: Model Hijacking-Resilient Federated Learning for Object Detection. CVPR 2023: 16343-16351 - [c24]Yanzhao Wu, Ka-Ho Chow, Wenqi Wei, Ling Liu:
Exploring Model Learning Heterogeneity for Boosting Ensemble Robustness. ICDM 2023: 648-657 - [c23]Wenqi Wei, Ka-Ho Chow, Fatih Ilhan, Yanzhao Wu, Ling Liu:
Model Cloaking against Gradient Leakage. ICDM 2023: 1403-1408 - [c22]Tiansheng Huang, Sihao Hu, Ka-Ho Chow, Fatih Ilhan, Selim F. Tekin, Ling Liu:
Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training. NeurIPS 2023 - [c21]Ka-Ho Chow, Umesh Deshpande, Veera Deenadhayalan, Sangeetha Seshadri, Ling Liu:
SCAD: Scalability Advisor for Interactive Microservices on Hybrid Clouds. SIGMOD Conference Companion 2023: 127-130 - [c20]Fatih Ilhan, Selim Furkan Tekin, Sihao Hu, Tiansheng Huang, Ka-Ho Chow, Ling Liu:
Hierarchical Deep Neural Network Inference for Device-Edge-Cloud Systems. WWW (Companion Volume) 2023: 302-305 - [i16]Fatih Ilhan, Ling Liu, Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, Myungjin Lee, Ramana Kompella, Hugo Latapie, Gaowen Liu:
EENet: Learning to Early Exit for Adaptive Inference. CoRR abs/2301.07099 (2023) - [i15]Ka-Ho Chow, Ling Liu, Wenqi Wei, Fatih Ilhan, Yanzhao Wu:
STDLens: Model Hijacking-Resilient Federated Learning for Object Detection. CoRR abs/2303.11511 (2023) - [i14]Wenqi Wei, Ling Liu, Jingya Zhou, Ka-Ho Chow, Yanzhao Wu:
Securing Distributed SGD against Gradient Leakage Threats. CoRR abs/2305.06473 (2023) - [i13]Yanzhao Wu, Ka-Ho Chow, Wenqi Wei, Ling Liu:
Exploring Model Learning Heterogeneity for Boosting Ensemble Robustness. CoRR abs/2310.02237 (2023) - [i12]Ka-Ho Chow, Umesh Deshpande, Veera Deenadhayalan, Sangeetha Seshadri, Ling Liu:
Atlas: Hybrid Cloud Migration Advisor for Interactive Microservices. CoRR abs/2311.06962 (2023) - [i11]Yanzhao Wu, Ka-Ho Chow, Wenqi Wei, Ling Liu:
Hierarchical Pruning of Deep Ensembles with Focal Diversity. CoRR abs/2311.10293 (2023) - 2022
- [j2]Mehmet Emre Gursoy, Ling Liu, Ka-Ho Chow, Stacey Truex, Wenqi Wei:
An Adversarial Approach to Protocol Analysis and Selection in Local Differential Privacy. IEEE Trans. Inf. Forensics Secur. 17: 1785-1799 (2022) - [c19]Ka-Ho Chow, Umesh Deshpande, Sangeetha Seshadri, Ling Liu:
DeepRest: deep resource estimation for interactive microservices. EuroSys 2022: 181-198 - [c18]Ka-Ho Chow, Ling Liu:
Boosting Object Detection Ensembles with Error Diversity. ICDM 2022: 903-908 - 2021
- [c17]Juhyun Bae, Ling Liu, Ka-Ho Chow, Yanzhao Wu, Gong Su, Arun Iyengar:
Transparent Network Memory Storage for Efficient Container Execution in Big Data Clouds. IEEE BigData 2021: 76-85 - [c16]Yanzhao Wu, Ling Liu, Zhongwei Xie, Ka-Ho Chow, Wenqi Wei:
Boosting Ensemble Accuracy by Revisiting Ensemble Diversity Metrics. CVPR 2021: 16469-16477 - [c15]Ka-Ho Chow, Ling Liu:
Robust Object Detection Fusion Against Deception. KDD 2021: 2703-2713 - [c14]Ka-Ho Chow, Umesh Deshpande, Sangeetha Seshadri, Ling Liu:
SRA: Smart Recovery Advisor for Cyber Attacks. SIGMOD Conference 2021: 2691-2695 - [c13]Ka-Ho Chow, Ling Liu:
Perception Poisoning Attacks in Federated Learning. TPS-ISA 2021: 146-155 - [c12]Stacey Truex, Ling Liu, Mehmet Emre Gursoy, Wenqi Wei, Ka-Ho Chow:
The TSC-PFed Architecture for Privacy-Preserving FL. TPS-ISA 2021: 207-216 - 2020
- [c11]Yanzhao Wu, Ling Liu, Zhongwei Xie, Juhyun Bae, Ka-Ho Chow, Wenqi Wei:
Promoting High Diversity Ensemble Learning with EnsembleBench. CogMI 2020: 208-217 - [c10]Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, Yanzhao Wu:
Understanding Object Detection Through an Adversarial Lens. ESORICS (2) 2020: 460-481 - [c9]Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, Yanzhao Wu:
A Framework for Evaluating Client Privacy Leakages in Federated Learning. ESORICS (1) 2020: 545-566 - [c8]Stacey Truex, Ling Liu, Ka-Ho Chow, Mehmet Emre Gursoy, Wenqi Wei:
LDP-Fed: federated learning with local differential privacy. EdgeSys@EuroSys 2020: 61-66 - [c7]Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, Yanzhao Wu:
Cross-Layer Strategic Ensemble Defense Against Adversarial Examples. ICNC 2020: 456-460 - [c6]Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, Yanzhao Wu:
Adversarial Deception in Deep Learning: Analysis and Mitigation. TPS-ISA 2020: 236-245 - [c5]Ka-Ho Chow, Ling Liu, Margaret Loper, Juhyun Bae, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, Yanzhao Wu:
Adversarial Objectness Gradient Attacks in Real-time Object Detection Systems. TPS-ISA 2020: 263-272 - [i10]Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, Yanzhao Wu:
TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems. CoRR abs/2004.04320 (2020) - [i9]Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, Yanzhao Wu:
A Framework for Evaluating Gradient Leakage Attacks in Federated Learning. CoRR abs/2004.10397 (2020) - [i8]Stacey Truex, Ling Liu, Ka-Ho Chow, Mehmet Emre Gursoy, Wenqi Wei:
LDP-Fed: Federated Learning with Local Differential Privacy. CoRR abs/2006.03637 (2020) - [i7]Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, Yanzhao Wu:
Understanding Object Detection Through An Adversarial Lens. CoRR abs/2007.05828 (2020) - [i6]Yanzhao Wu, Ling Liu, Zhongwei Xie, Juhyun Bae, Ka-Ho Chow, Wenqi Wei:
Promoting High Diversity Ensemble Learning with EnsembleBench. CoRR abs/2010.10623 (2020)
2010 – 2019
- 2019
- [j1]Ka Ho Chow, Suining He, Jiajie Tan, S.-H. Gary Chan:
Efficient Locality Classification for Indoor Fingerprint-Based Systems. IEEE Trans. Mob. Comput. 18(2): 290-304 (2019) - [c4]Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, Ling Liu:
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks. IEEE BigData 2019: 1282-1291 - [c3]Yanzhao Wu, Ling Liu, Juhyun Bae, Ka-Ho Chow, Arun Iyengar, Calton Pu, Wenqi Wei, Lei Yu, Qi Zhang:
Demystifying Learning Rate Policies for High Accuracy Training of Deep Neural Networks. IEEE BigData 2019: 1971-1980 - [c2]Lei Yu, Qi Zhang, Donna Dillenberger, Ling Liu, Calton Pu, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, Hong Min, Arun Iyengar, Gong Su:
GRAHIES: Multi-Scale Graph Representation Learning with Latent Hierarchical Structure. CogMI 2019: 8-15 - [c1]Ling Liu, Wenqi Wei, Ka-Ho Chow, Margaret Loper, Mehmet Emre Gursoy, Stacey Truex, Yanzhao Wu:
Deep Neural Network Ensembles Against Deception: Ensemble Diversity, Accuracy and Robustness. MASS 2019: 274-282 - [i5]Yifeng Zhang, Ka Ho Chow, S.-H. Gary Chan:
DA-LSTM: A Long Short-Term Memory with Depth Adaptive to Non-uniform Information Flow in Sequential Data. CoRR abs/1903.02082 (2019) - [i4]Yanzhao Wu, Ling Liu, Juhyun Bae, Ka-Ho Chow, Arun Iyengar, Calton Pu, Wenqi Wei, Lei Yu, Qi Zhang:
Demystifying Learning Rate Polices for High Accuracy Training of Deep Neural Networks. CoRR abs/1908.06477 (2019) - [i3]Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, Ling Liu:
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks. CoRR abs/1908.07667 (2019) - [i2]Ling Liu, Wenqi Wei, Ka-Ho Chow, Margaret Loper, Mehmet Emre Gursoy, Stacey Truex, Yanzhao Wu:
Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness. CoRR abs/1908.11091 (2019) - [i1]Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, Yanzhao Wu:
Cross-Layer Strategic Ensemble Defense Against Adversarial Examples. CoRR abs/1910.01742 (2019)
Coauthor Index
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