Changchang Liu

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 41

Top Topics

Machine Learning

Abnormality Detection

Top Venues

Proc. Priv. Enhancing Technol.

Publications

Tianyu Cui, Shiyu Ma, Ziang Chen, Tong Xiao, Shimin Tao, Yilun Liu, Shenglin Zhang, Duoming Lin, Changchang Liu, Yuzhe Cai, Weibin Meng, Yongqian Sun, Dan Pei
LogEval: A Comprehensive Benchmark Suite for Large Language Models In Log Analysis. CoRR (2024)
Maeda F. Hanafi, Frederick Reiss, Yannis Katsis, Robert Moore, David Wood, Mohammad Hassan Falakmasir, Changchang Liu
Machine-Assisted Error Discovery in Conversational AI Systems. CHI Extended Abstracts (2024)
Tianshu Zhang, Changchang Liu, Wei-Han Lee, Yu Su, Huan Sun
Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms. ACL (1) (2023)
Changchang Liu, Peter Kutchukian, Nhan D. Nguyen, Mohammed Alquraishi, Peter K. Sorger
A Hybrid Structure-Based Machine Learning Approach for Predicting Kinase Inhibition by Small Molecules. J. Chem. Inf. Model. 63 (17) (2023)
Tianshu Zhang, Changchang Liu, Wei-Han Lee, Yu Su, Huan Sun
Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms. CoRR (2023)
Lirong Fu, Shouling Ji, Changchang Liu, Peiyu Liu, Fuzheng Duan, Zonghui Wang, Whenzhi Chen, Ting Wang
Focus : Function clone identification on cross-platform. Int. J. Intell. Syst. 37 (8) (2022)
Hanlin Lu, Changchang Liu, Shiqiang Wang, Ting He, Vijay Narayanan, Kevin S. Chan, Stephen Pasteris
Joint Coreset Construction and Quantization for Distributed Machine Learning. CoRR (2022)
Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Mehrdad Mahdavi, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris
Communication-Efficient $k$k-Means for Edge-Based Machine Learning. IEEE Trans. Parallel Distributed Syst. 33 (10) (2022)
Haiqin Weng, Shouling Ji, Changchang Liu, Ting Wang, Qinming He, Jianhai Chen
Fast-RCM: Fast Tree-Based Unsupervised Rare-Class Mining. IEEE Trans. Cybern. 51 (10) (2021)
Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Mehrdad Mahdavi, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris
Communication-efficient k-Means for Edge-based Machine Learning. CoRR (2021)
Matthew E. Berginski, Nienke Moret, Changchang Liu, Dennis Goldfarb, Peter K. Sorger, Shawn M. Gomez
The Dark Kinase Knowledgebase: an online compendium of knowledge and experimental results of understudied kinases. Nucleic Acids Res. 49 (Database-Issue) (2021)
Linkang Du, Zhikun Zhang, Shaojie Bai, Changchang Liu, Shouling Ji, Peng Cheng, Jiming Chen
AHEAD: Adaptive Hierarchical Decomposition for Range Query under Local Differential Privacy. CCS (2021)
Linkang Du, Zhikun Zhang, Shaojie Bai, Changchang Liu, Shouling Ji, Peng Cheng, Jiming Chen
AHEAD: Adaptive Hierarchical Decomposition for Range Query under Local Differential Privacy. CoRR (2021)
Qianjun Liu, Shouling Ji, Changchang Liu, Chunming Wu
A Practical Black-Box Attack on Source Code Authorship Identification Classifiers. IEEE Trans. Inf. Forensics Secur. 16 (2021)
Wei-Han Lee, Steve Millman, Nirmit Desai, Mudhakar Srivatsa, Changchang Liu
NeuralFP: Out-of-distribution Detection using Fingerprints of Neural Networks. ICPR (2020)
Tiffany Tuor, Shiqiang Wang, Bong Jun Ko, Changchang Liu, Kin K. Leung
Data Selection for Federated Learning with Relevant and Irrelevant Data at Clients. CoRR (2020)
Hanlin Lu, Changchang Liu, Ting He, Shiqiang Wang, Kevin S. Chan
Sharing Models or Coresets: A Study based on Membership Inference Attack. CoRR (2020)
Tiffany Tuor, Shiqiang Wang, Bong Jun Ko, Changchang Liu, Kin K. Leung
Overcoming Noisy and Irrelevant Data in Federated Learning. ICPR (2020)
Hanlin Lu, Changchang Liu, Shiqiang Wang, Ting He, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris
Joint Coreset Construction and Quantization for Distributed Machine Learning. Networking (2020)
Chenghui Shi, Shouling Ji, Qianjun Liu, Changchang Liu, Yuefeng Chen, Yuan He, Zhe Liu, Raheem Beyah, Ting Wang
Text Captcha Is Dead? A Large Scale Deployment and Empirical Study. CCS (2020)
Jing Ke, Changchang Liu, Yizhou Lu, Naifeng Jing, Xiaoyao Liang, Fusong Jiang
FIMIL : A high-throughput deep learning model for abnormality detection with weak annotation in microscopy images. ACSW (2020)
Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Mehrdad Mahdavi, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris
Communication-efficient k-Means for Edge-based Machine Learning. ICDCS (2020)
Chengkun Wei, Shouling Ji, Changchang Liu, Wenzhi Chen, Ting Wang
AsgLDP: Collecting and Generating Decentralized Attributed Graphs With Local Differential Privacy. IEEE Trans. Inf. Forensics Secur. 15 (2020)
Changchang Liu, Wei-Han Lee, Seraphin B. Calo
Neuraltran: Optimal Data Transformation for Privacy-Preserving Machine Learning by Leveraging Neural Networks. DSN (Supplements) (2020)
Jing Ke, Zhaoming Jiang, Changchang Liu, Tomasz Bednarz, Arcot Sowmya, Xiaoyao Liang
Selective Detection and Segmentation of Cervical Cells. ICBBT (2019)
Changchang Liu, Xi He, Thee Chanyaswad, Shiqiang Wang, Prateek Mittal
Investigating Statistical Privacy Frameworks from the Perspective of Hypothesis Testing. Proc. Priv. Enhancing Technol. 2019 (3) (2019)
Thee Chanyaswad, Changchang Liu, Prateek Mittal
RON-Gauss: Enhancing Utility in Non-Interactive Private Data Release. Proc. Priv. Enhancing Technol. 2019 (1) (2019)
Wei-Han Lee, Bong Jun Ko, Shiqiang Wang, Changchang Liu, Kin K. Leung
Exact Incremental and Decremental Learning for LS-SVM. ICIP (2019)
Changchang Liu, Supriyo Chakraborty, Dinesh C. Verma
Secure Model Fusion for Distributed Learning Using Partial Homomorphic Encryption. PADG@ESORICS (2018)
Wei-Han Lee, Changchang Liu, Shouling Ji, Prateek Mittal, Ruby B. Lee
Blind De-anonymization Attacks using Social Networks. CoRR (2018)
Chongsheng Zhang, George Almpanidis, Wanwan Wang, Changchang Liu
An empirical evaluation of high utility itemset mining algorithms. Expert Syst. Appl. 101 (2018)
Wei-Han Lee, Changchang Liu, Shouling Ji, Prateek Mittal, Ruby B. Lee
Quantification of De-anonymization Risks in Social Networks. ICISSP (2017)
Wei-Han Lee, Changchang Liu, Shouling Ji, Prateek Mittal, Ruby B. Lee
How to Quantify Graph De-anonymization Risks. ICISSP (Revised Selected Papers) (2017)
Changchang Liu, Supriyo Chakraborty, Prateek Mittal
DEEProtect: Enabling Inference-based Access Control on Mobile Sensing Applications. CoRR (2017)
Wei-Han Lee, Changchang Liu, Shouling Ji, Prateek Mittal, Ruby B. Lee
Blind De-anonymization Attacks using Social Networks. WPES@CCS (2017)
Chongsheng Zhang, Changchang Liu, Xiangliang Zhang, George Almpanidis
An up-to-date comparison of state-of-the-art classification algorithms. Expert Syst. Appl. 82 (2017)
Wei-Han Lee, Changchang Liu, Shouling Ji, Prateek Mittal, Ruby B. Lee
Quantification of De-anonymization Risks in Social Networks. CoRR (2017)
Thee Chanyaswad, Changchang Liu, Prateek Mittal
Coupling Dimensionality Reduction with Generative Model for Non-Interactive Private Data Release. CoRR (2017)
Changchang Liu, Prateek Mittal
LinkMirage: Enabling Privacy-preserving Analytics on Social Relationships. NDSS (2016)
Changchang Liu, Supriyo Chakraborty, Prateek Mittal
Dependence Makes You Vulnberable: Differential Privacy Under Dependent Tuples. NDSS (2016)
Chongsheng Zhang, Jingjun Bi, Changchang Liu, Ke Chen
A parameter-free label propagation algorithm for person identification in stereo videos. Neurocomputing 218 (2016)
Changchang Liu, Peng Gao, Matthew K. Wright, Prateek Mittal
Exploiting Temporal Dynamics in Sybil Defenses. CCS (2015)
Changchang Liu, Prateek Mittal
LinkMirage: How to Anonymize Links in Dynamic Social Systems. CoRR (2015)
Shouling Ji, Shukun Yang, Ting Wang, Changchang Liu, Wei-Han Lee, Raheem A. Beyah
PARS: A Uniform and Open-source Password Analysis and Research System. ACSAC (2015)
Changchang Liu, Weidong Chen
Sparse Self-Calibration Imaging via Iterative MAP in FM-Based Distributed Passive Radar. IEEE Geosci. Remote. Sens. Lett. 10 (3) (2013)
Li Ding, Changchang Liu, Weidong Chen
Analyzing the FD-MIMO sparse imaging under carrier frequency offsets from the perspective of point spread function. ACSSC (2013)
Xuezhi He, Changchang Liu, Bo Liu, Dongjin Wang
Sparse Frequency Diverse MIMO Radar Imaging for Off-Grid Target Based on Adaptive Iterative MAP. Remote. Sens. 5 (2) (2013)
Changchang Liu, Tianyun Wang, Li Ding, Weidong Chen
Sparse imaging for passive radar system based on digital video broadcasting satellites. WCSP (2012)
Li Ding, Changchang Liu, Weidong Chen, Wenyi Zhang
Sparsity-driven high resolution FDLFM-MIMO radar imaging. WCSP (2012)
Changchang Liu, Jin Yan, Weidong Chen
Sparse self-calibration by map method for MIMO radar imaging. ICASSP (2012)
Changchang Liu, Weidong Chen
Sparse frequency diverse MIMO radar imaging. ACSCC (2012)
Changchang Liu, Li Ding, Weidong Chen
A correction and generalization to the sparse learning via iterative minimization method for target off the grid in MIMO radar imaging. ACSCC (2012)