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ORCIDYanzhao Wu 0001
Person information
- unicode name: 吴彦钊
- affiliation: Florida International University, School of Computing and Information Sciences, Miami, FL, USA
- affiliation (PhD 2022): Georgia Institute of Technology, School of Computer Science, Atlanta, GA, USA
Other persons with the same name
- Yanzhao Wu 0002 — Chinese Academy and Sciences, Centre for Earth Observation and Digital Earth, Beijing, China
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Books and Theses
- 2023
[b1]Yanzhao Wu:
Towards Deep Learning System and Algorithm Co-design. Georgia Institute of Technology, Atlanta, GA, USA, 2023
Journal Articles
- 2024
- [j7]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) - [j6]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) - 2023
- [j5]Yanzhao Wu, Ling Liu:
Selecting and Composing Learning Rate Policies for Deep Neural Networks. ACM Trans. Intell. Syst. Technol. 14(2): 22:1-22:25 (2023) - [j4]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) - 2022
- [j3]Zhongwei Xie, Ling Liu, Yanzhao Wu, Luo Zhong, Lin Li:
Learning Text-image Joint Embedding for Efficient Cross-modal Retrieval with Deep Feature Engineering. ACM Trans. Inf. Syst. 40(4): 74:1-74:27 (2022) - [j2]Yanzhao Wu, Ling Liu, Calton Pu, Wenqi Cao, Semih Sahin, Wenqi Wei, Qi Zhang:
A Comparative Measurement Study of Deep Learning as a Service Framework. IEEE Trans. Serv. Comput. 15(1): 551-566 (2022) - [j1]Zhongwei Xie, Ling Liu, Yanzhao Wu, Lin Li, Luo Zhong:
Learning TFIDF Enhanced Joint Embedding for Recipe-Image Cross-Modal Retrieval Service. IEEE Trans. Serv. Comput. 15(6): 3304-3316 (2022)
Conference and Workshop Papers
- 2024
- [c30]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 - 2023
- [c29]Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu:
Privacy Risks Analysis and Mitigation in Federated Learning for Medical Images. BIBM 2023: 1870-1873 - [c28]Sanjana Vijay Ganesh, Yanzhao Wu, Gaowen Liu, Ramana Kompella, Ling Liu:
Amplifying Object Tracking Performance on Edge Devices. CogMI 2023: 83-92 - [c27]Hongpeng Jin, Wenqi Wei, Xuyu Wang, Wenbin Zhang, Yanzhao Wu:
Rethinking Learning Rate Tuning in the Era of Large Language Models. CogMI 2023: 112-121 - [c26]Ka Ho Chow, Ling Liu, Wenqi Wei, Fatih Ilhan, Yanzhao Wu:
STDLens: Model Hijacking-Resilient Federated Learning for Object Detection. CVPR 2023: 16343-16351 - [c25]Yanzhao Wu, Ka Ho Chow, Wenqi Wei, Ling Liu:
Exploring Model Learning Heterogeneity for Boosting Ensemble Robustness. ICDM 2023: 648-657 - [c24]Wenqi Wei, Ka-Ho Chow, Fatih Ilhan, Yanzhao Wu, Ling Liu:
Model Cloaking against Gradient Leakage. ICDM 2023: 1403-1408 - [c23]Xirong Cao, Xiang Li, Divyesh Jadav, Yanzhao Wu, Zhehui Chen, Chen Zeng, Wenqi Wei:
Invisible Watermarking for Audio Generation Diffusion Models. TPS-ISA 2023: 193-202 - 2021
- [c22]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 - [c21]Yanzhao Wu, Ling Liu, Ramana Kompella:
Parallel Detection for Efficient Video Analytics at the Edge. CogMI 2021: 1-10 - [c20]Juhyun Bae, Ling Liu, Yanzhao Wu, Gong Su, Arun Iyengar:
RDMAbox: Optimizing RDMA for Memory Intensive Workload. CIC 2021: 1-10 - [c19]Yanzhao Wu, Ling Liu, Zhongwei Xie, Ka Ho Chow, Wenqi Wei:
Boosting Ensemble Accuracy by Revisiting Ensemble Diversity Metrics. CVPR 2021: 16469-16477 - [c18]Wenqi Wei, Ling Liu, Yanzhao Wu, Gong Su, Arun Iyengar:
Gradient-Leakage Resilient Federated Learning. ICDCS 2021: 797-807 - [c17]Yanzhao Wu, Ling Liu:
Boosting Deep Ensemble Performance with Hierarchical Pruning. ICDM 2021: 1433-1438 - 2020
- [c16]Zhongwei Xie, Ling Liu, Yanzhao Wu, Lin Li, Luo Zhong:
Cross-Modal Joint Embedding with Diverse Semantics. CogMI 2020: 157-166 - [c15]Yanzhao Wu, Ling Liu, Zhongwei Xie, Juhyun Bae, Ka Ho Chow, Wenqi Wei:
Promoting High Diversity Ensemble Learning with EnsembleBench. CogMI 2020: 208-217 - [c14]Semih Sahin, Ling Liu, Wenqi Cao, Qi Zhang, Juhyun Bae, Yanzhao Wu:
Memory Abstraction and Optimization for Distributed Executors. CIC 2020: 78-87 - [c13]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 - [c12]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 - [c11]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 - [c10]Juhyun Bae, Gong Su, Arun Iyengar, Yanzhao Wu, Ling Liu:
Efficient Orchestration of Host and Remote Shared Memory for Memory Intensive Workloads. MEMSYS 2020: 194-208 - [c9]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 - [c8]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 - 2019
- [c7]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 - [c6]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 - [c5]Ling Liu, Wenqi Cao, Semih Sahin, Qi Zhang, Juhyun Bae, Yanzhao Wu:
Memory Disaggregation: Research Problems and Opportunities. ICDCS 2019: 1664-1673 - [c4]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 - 2018
- [c3]Yanzhao Wu, Wenqi Cao, Semih Sahin, Ling Liu:
Experimental Characterizations and Analysis of Deep Learning Frameworks. IEEE BigData 2018: 372-377 - [c2]Ling Liu, Yanzhao Wu, Wenqi Wei, Wenqi Cao, Semih Sahin, Qi Zhang:
Benchmarking Deep Learning Frameworks: Design Considerations, Metrics and Beyond. ICDCS 2018: 1258-1269 - [c1]Pengcheng Wang, Jeffrey Svajlenko, Yanzhao Wu, Yun Xu, Chanchal K. Roy:
CCAligner: a token based large-gap clone detector. ICSE 2018: 1066-1077
Informal and Other Publications
- 2024
- [i26]Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu:
Security and Privacy Challenges of Large Language Models: A Survey. CoRR abs/2402.00888 (2024) - 2023
- [i25]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) - [i24]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) - [i23]Wenqi Wei, Ling Liu, Jingya Zhou, Ka Ho Chow, Yanzhao Wu:
Securing Distributed SGD against Gradient Leakage Threats. CoRR abs/2305.06473 (2023) - [i22]Sanjana Vijay Ganesh, Yanzhao Wu, Gaowen Liu, Ramana Kompella, Ling Liu:
Fast and Resource-Efficient Object Tracking on Edge Devices: A Measurement Study. CoRR abs/2309.02666 (2023) - [i21]Hongpeng Jin, Wenqi Wei, Xuyu Wang, Wenbin Zhang, Yanzhao Wu:
Rethinking Learning Rate Tuning in the Era of Large Language Models. CoRR abs/2309.08859 (2023) - [i20]Xirong Cao, Xiang Li, Divyesh Jadav, Yanzhao Wu, Zhehui Chen, Chen Zeng, Wenqi Wei:
Invisible Watermarking for Audio Generation Diffusion Models. CoRR abs/2309.13166 (2023) - [i19]Yanzhao Wu, Ka Ho Chow, Wenqi Wei, Ling Liu:
Exploring Model Learning Heterogeneity for Boosting Ensemble Robustness. CoRR abs/2310.02237 (2023) - [i18]Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu:
Privacy Risks Analysis and Mitigation in Federated Learning for Medical Images. CoRR abs/2311.06643 (2023) - [i17]Yanzhao Wu, Ka Ho Chow, Wenqi Wei, Ling Liu:
Hierarchical Pruning of Deep Ensembles with Focal Diversity. CoRR abs/2311.10293 (2023) - 2022
- [i16]Yanzhao Wu, Ling Liu:
Selecting and Composing Learning Rate Policies for Deep Neural Networks. CoRR abs/2210.12936 (2022) - 2021
- [i15]Juhyun Bae, Gong Su, Arun Iyengar, Yanzhao Wu, Ling Liu:
RDMAbox : Optimizing RDMA for Memory Intensive Workloads. CoRR abs/2104.12197 (2021) - [i14]Wenqi Wei, Ling Liu, Yanzhao Wu, Gong Su, Arun Iyengar:
Gradient-Leakage Resilient Federated Learning. CoRR abs/2107.01154 (2021) - [i13]Yanzhao Wu, Ling Liu, Ramana Kompella:
Parallel Detection for Efficient Video Analytics at the Edge. CoRR abs/2107.12563 (2021) - [i12]Zhongwei Xie, Ling Liu, Yanzhao Wu, Lin Li, Luo Zhong:
Learning TFIDF Enhanced Joint Embedding for Recipe-Image Cross-Modal Retrieval Service. CoRR abs/2108.00724 (2021) - [i11]Zhongwei Xie, Ling Liu, Yanzhao Wu, Luo Zhong, Lin Li:
Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering. CoRR abs/2110.11592 (2021) - 2020
- [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]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) - [i7]Juhyun Bae, Gong Su, Arun Iyengar, Yanzhao Wu, Ling Liu:
Efficient Orchestration of Host and Remote Shared Memory for Memory Intensive Workloads. CoRR abs/2008.00902 (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) - 2019
- [i5]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) - [i4]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) - [i3]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) - [i2]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) - 2018
- [i1]Yanzhao Wu, Ling Liu, Calton Pu, Wenqi Cao, Semih Sahin, Wenqi Wei, Qi Zhang:
A Comparative Measurement Study of Deep Learning as a Service Framework. CoRR abs/1810.12210 (2018)
Coauthor Index
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