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Changchang Liu
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2020 – today
- 2024
- [c26]Maeda F. Hanafi
, Frederick Reiss
Machine-Assisted Error Discovery in Conversational AI Systems. CHI Extended Abstracts 2024: 234:1-234:10 - [i12]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 abs/2407.01896 (2024) - 2023
- [j14]Changchang Liu
A Hybrid Structure-Based Machine Learning Approach for Predicting Kinase Inhibition by Small Molecules. J. Chem. Inf. Model. 63(17): 5457-5472 (2023) - [c25]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: 12149-12163 - [i11]Tianshu Zhang, Changchang Liu, Wei-Han Lee, Yu Su, Huan Sun:
Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms. CoRR abs/2305.17221 (2023) - 2022
- [j13]Lirong Fu
Focus : Function clone identification on cross-platform. Int. J. Intell. Syst. 37(8): 5082-5112 (2022) - [j12]Hanlin Lu
Communication-Efficient $k$k-Means for Edge-Based Machine Learning. IEEE Trans. Parallel Distributed Syst. 33(10): 2509-2523 (2022) - [i10]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 abs/2204.06652 (2022) - 2021
- [j11]Matthew E. Berginski
The Dark Kinase Knowledgebase: an online compendium of knowledge and experimental results of understudied kinases. Nucleic Acids Res. 49(Database-Issue): D529-D535 (2021) - [j10]Haiqin Weng
Fast-RCM: Fast Tree-Based Unsupervised Rare-Class Mining. IEEE Trans. Cybern. 51(10): 5198-5211 (2021) - [j9]Qianjun Liu
A Practical Black-Box Attack on Source Code Authorship Identification Classifiers. IEEE Trans. Inf. Forensics Secur. 16: 3620-3633 (2021) - [c24]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: 1266-1288 - [i9]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 abs/2102.04282 (2021) - [i8]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 abs/2110.07505 (2021) - 2020
- [j8]Chengkun Wei
AsgLDP: Collecting and Generating Decentralized Attributed Graphs With Local Differential Privacy. IEEE Trans. Inf. Forensics Secur. 15: 3239-3254 (2020) - [c23]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: 34:1-34:6 - [c22]Chenghui Shi, Shouling Ji, Qianjun Liu, Changchang Liu, Yuefeng Chen, Yuan He, Zhe Liu, Raheem Beyah
Text Captcha Is Dead? A Large Scale Deployment and Empirical Study. CCS 2020: 1391-1406 - [c21]Changchang Liu, Wei-Han Lee, Seraphin B. Calo:
Neuraltran: Optimal Data Transformation for Privacy-Preserving Machine Learning by Leveraging Neural Networks. DSN (Supplements) 2020: 21-24 - [c20]Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Mehrdad Mahdavi, Vijaykrishnan Narayanan
Communication-efficient k-Means for Edge-based Machine Learning. ICDCS 2020: 595-605 - [c19]Tiffany Tuor, Shiqiang Wang, Bong Jun Ko, Changchang Liu, Kin K. Leung:
Overcoming Noisy and Irrelevant Data in Federated Learning. ICPR 2020: 5020-5027 - [c18]Wei-Han Lee, Steve Millman, Nirmit Desai, Mudhakar Srivatsa, Changchang Liu:
NeuralFP: Out-of-distribution Detection using Fingerprints of Neural Networks. ICPR 2020: 9561-9568 - [c17]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: 172-180 - [i7]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 abs/2001.08300 (2020) - [i6]Hanlin Lu, Changchang Liu, Ting He, Shiqiang Wang, Kevin S. Chan:
Sharing Models or Coresets: A Study based on Membership Inference Attack. CoRR abs/2007.02977 (2020)
2010 – 2019
- 2019
- [b1]Changchang Liu:
Rethinking the Science of Statistical Privacy. Princeton University, USA, 2019 - [j7]Thee Chanyaswad, Changchang Liu, Prateek Mittal:
RON-Gauss: Enhancing Utility in Non-Interactive Private Data Release. Proc. Priv. Enhancing Technol. 2019(1): 26-46 (2019) - [j6]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): 233-254 (2019) - [c16]Jing Ke, Zhaoming Jiang, Changchang Liu, Tomasz Bednarz, Arcot Sowmya, Xiaoyao Liang:
Selective Detection and Segmentation of Cervical Cells. ICBBT 2019: 55-61 - [c15]Wei-Han Lee, Bong Jun Ko, Shiqiang Wang, Changchang Liu, Kin K. Leung:
Exact Incremental and Decremental Learning for LS-SVM. ICIP 2019: 2334-2338 - 2018
- [j5]Chongsheng Zhang, George Almpanidis
An empirical evaluation of high utility itemset mining algorithms. Expert Syst. Appl. 101: 91-115 (2018) - [c14]Changchang Liu, Supriyo Chakraborty, Dinesh C. Verma:
Secure Model Fusion for Distributed Learning Using Partial Homomorphic Encryption. PADG@ESORICS 2018: 154-179 - [i5]Wei-Han Lee, Changchang Liu, Shouling Ji, Prateek Mittal, Ruby B. Lee:
Blind De-anonymization Attacks using Social Networks. CoRR abs/1801.05534 (2018) - 2017
- [j4]Chongsheng Zhang, Changchang Liu, Xiangliang Zhang
An up-to-date comparison of state-of-the-art classification algorithms. Expert Syst. Appl. 82: 128-150 (2017) - [c13]Wei-Han Lee, Changchang Liu, Shouling Ji, Prateek Mittal, Ruby B. Lee:
How to Quantify Graph De-anonymization Risks. ICISSP (Revised Selected Papers) 2017: 84-104 - [c12]Wei-Han Lee, Changchang Liu, Shouling Ji, Prateek Mittal, Ruby B. Lee:
Quantification of De-anonymization Risks in Social Networks. ICISSP 2017: 126-135 - [c11]Wei-Han Lee, Changchang Liu, Shouling Ji, Prateek Mittal, Ruby B. Lee:
Blind De-anonymization Attacks using Social Networks. WPES@CCS 2017: 1-4 - [i4]Changchang Liu, Supriyo Chakraborty, Prateek Mittal:
DEEProtect: Enabling Inference-based Access Control on Mobile Sensing Applications. CoRR abs/1702.06159 (2017) - [i3]Wei-Han Lee, Changchang Liu, Shouling Ji, Prateek Mittal, Ruby B. Lee:
Quantification of De-anonymization Risks in Social Networks. CoRR abs/1703.04873 (2017) - [i2]Thee Chanyaswad, Changchang Liu, Prateek Mittal:
Coupling Dimensionality Reduction with Generative Model for Non-Interactive Private Data Release. CoRR abs/1709.00054 (2017) - 2016
- [j3]Chongsheng Zhang, Jingjun Bi, Changchang Liu, Ke Chen
A parameter-free label propagation algorithm for person identification in stereo videos. Neurocomputing 218: 72-78 (2016) - [c10]Changchang Liu, Prateek Mittal:
LinkMirage: Enabling Privacy-preserving Analytics on Social Relationships. NDSS 2016 - [c9]Changchang Liu, Supriyo Chakraborty, Prateek Mittal:
Dependence Makes You Vulnberable: Differential Privacy Under Dependent Tuples. NDSS 2016 - 2015
- [c8]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: 321-330 - [c7]Changchang Liu, Peng Gao, Matthew K. Wright
Exploiting Temporal Dynamics in Sybil Defenses. CCS 2015: 805-816 - [i1]Changchang Liu, Prateek Mittal:
LinkMirage: How to Anonymize Links in Dynamic Social Systems. CoRR abs/1501.01361 (2015) - 2013
- [j2]Changchang Liu, Weidong Chen:
Sparse Self-Calibration Imaging via Iterative MAP in FM-Based Distributed Passive Radar. IEEE Geosci. Remote. Sens. Lett. 10(3): 538-542 (2013) - [j1]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): 631-647 (2013) - [c6]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: 200-204 - 2012
- [c5]Changchang Liu, Weidong Chen:
Sparse frequency diverse MIMO radar imaging. ACSCC 2012: 853-857 - [c4]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: 895-899 - [c3]Changchang Liu, Jin Yan, Weidong Chen:
Sparse self-calibration by map method for MIMO radar imaging. ICASSP 2012: 2469-2472 - [c2]Li Ding, Changchang Liu, Weidong Chen, Wenyi Zhang:
Sparsity-driven high resolution FDLFM-MIMO radar imaging. WCSP 2012: 1-5 - [c1]Changchang Liu, Tianyun Wang, Li Ding, Weidong Chen:
Sparse imaging for passive radar system based on digital video broadcasting satellites. WCSP 2012: 1-5
Coauthor Index
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last updated on 2024-08-20 20:25 CEST by the dblp team
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