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Wenxin Jiang
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2020 – today
- 2024
- [i14]Wenxin Jiang, Jerin Yasmin, Jason Jones, Nicholas Synovic, Jiashen Kuo, Nathaniel Bielanski, Yuan Tian, George K. Thiruvathukal, James C. Davis:
PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software. CoRR abs/2402.00699 (2024) - 2023
- [c23]Wenxin Jiang, Nicholas Synovic, Matt Hyatt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis:
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry. ICSE 2023: 2463-2475 - [c22]James C. Davis, Purvish Jajal, Wenxin Jiang, Taylor R. Schorlemmer, Nicholas Synovic, George K. Thiruvathukal:
Reusing Deep Learning Models: Challenges and Directions in Software Engineering. JVA 2023: 17-30 - [c21]Wenxin Jiang, Nicholas Synovic, Purvish Jajal, Taylor R. Schorlemmer, Arav Tewari, Bhavesh Pareek, George K. Thiruvathukal, James C. Davis:
PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages. MSR 2023: 57-61 - [i13]Diego Montes, Pongpatapee Peerapatanapokin, Jeff Schultz, Chengjun Guo, Wenxin Jiang, James C. Davis:
Discrepancies among Pre-trained Deep Neural Networks: A New Threat to Model Zoo Reliability. CoRR abs/2303.02551 (2023) - [i12]Wenxin Jiang, Nicholas Synovic, Matt Hyatt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis:
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry. CoRR abs/2303.02552 (2023) - [i11]Wenxin Jiang, Vishnu Banna, Naveen Vivek, Abhinav Goel, Nicholas Synovic, George K. Thiruvathukal, James C. Davis:
Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Vision. CoRR abs/2303.07476 (2023) - [i10]Wenxin Jiang, Nicholas Synovic, Purvish Jajal, Taylor R. Schorlemmer, Arav Tewari, Bhavesh Pareek, George K. Thiruvathukal, James C. Davis:
PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages. CoRR abs/2303.08934 (2023) - [i9]Purvish Jajal, Wenxin Jiang, Arav Tewari, Joseph Woo, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis:
Analysis of Failures and Risks in Deep Learning Model Converters: A Case Study in the ONNX Ecosystem. CoRR abs/2303.17708 (2023) - [i8]Wenxin Jiang, Chingwo Cheung, George K. Thiruvathukal, James C. Davis:
Exploring Naming Conventions (and Defects) of Pre-trained Deep Learning Models in Hugging Face and Other Model Hubs. CoRR abs/2310.01642 (2023) - [i7]Wenxin Jiang, Jason Jones, Jerin Yasmin, Nicholas Synovic, Rajeev Sashti, Sophie Chen, George K. Thiruvathukal, Yuan Tian, James C. Davis:
PeaTMOSS: Mining Pre-Trained Models in Open-Source Software. CoRR abs/2310.03620 (2023) - 2022
- [j23]Wenxin Jiang, Guochang Zhu, Yiyun Shen, Qian Xie, Min Ji, Yongtao Yu:
An Empirical Mode Decomposition Fuzzy Forecast Model for Air Quality. Entropy 24(12): 1803 (2022) - [j22]Haiyang Li, Wenxin Jiang, Jin Deng, Ruien Yu, Qianghua Pan:
A Sensitive Frequency Range Method Based on Laser Ultrasounds for Micro-Crack Depth Determination. Sensors 22(19): 7221 (2022) - [j21]Bolun Chen, Wenxin Jiang, Yong-Tao Yu, Lei Zhou, Claudio J. Tessone:
Graph embedding based ant colony optimization for negative influence propagation suppression under cost constraints. Swarm Evol. Comput. 72: 101102 (2022) - [c20]Wenxin Jiang, Bolun Chen, Zifan Qi, Yongtao Yu:
Link Prediction Based on Sampled Single Vertices. ICAIS (1) 2022: 17-27 - [c19]Nicholas M. Synovic, Matt Hyatt, Rohan Sethi, Sohini Thota, Shilpika, Allan J. Miller, Wenxin Jiang, Emmanuel S. Amobi, Austin Pinderski, Konstantin Läufer, Nicholas J. Hayward, Neil Klingensmith, James C. Davis, George K. Thiruvathukal:
Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics. ASE 2022: 167:1-167:4 - [c18]Wenxin Jiang, Nicholas Synovic, Rohan Sethi, Aryan Indarapu, Matt Hyatt, Taylor R. Schorlemmer, George K. Thiruvathukal, James C. Davis:
An Empirical Study of Artifacts and Security Risks in the Pre-trained Model Supply Chain. SCORED@CCS 2022: 105-114 - [c17]Diego Montes, Pongpatapee Peerapatanapokin, Jeff Schultz, Chengjun Guo, Wenxin Jiang, James C. Davis:
Discrepancies among pre-trained deep neural networks: a new threat to model zoo reliability. ESEC/SIGSOFT FSE 2022: 1605-1609 - [c16]Jakob Veselsky, Jack West, Isaac Ahlgren, George K. Thiruvathukal, Neil Klingensmith, Abhinav Goel, Wenxin Jiang, James C. Davis, Kyuin Lee, Younghyun Kim:
Establishing trust in vehicle-to-vehicle coordination: a sensor fusion approach. HotMobile 2022: 128 - [i6]Nicholas Synovic, Matt Hyatt, Rohan Sethi, Sohini Thota, Shilpika, Allan J. Miller, Wenxin Jiang, Emmanuel S. Amobi, Austin Pinderski, Konstantin Läufer, Nicholas J. Hayward, Neil Klingensmith, James C. Davis, George K. Thiruvathukal:
Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics. CoRR abs/2207.11767 (2022) - 2021
- [j20]Yang Xu, Hongmei Jiang, Wenxin Jiang:
Extended graphical lasso for multiple interaction networks for high dimensional omics data. PLoS Comput. Biol. 17(10) (2021) - [c15]Wenxin Jiang:
Research on the construction and application of College Ideology network system based on Data Mining. ICISCAE (ACM) 2021: 2430-2434 - [i5]Vishnu Banna, Akhil Chinnakotla, Zhengxin Yan, Anirudh Vegesana, Naveen Vivek, Kruthi Krishnappa, Wenxin Jiang, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis:
An Experience Report on Machine Learning Reproducibility: Guidance for Practitioners and TensorFlow Model Garden Contributors. CoRR abs/2107.00821 (2021) - [i4]Wei Ju, Wenxin Jiang:
A Note on Comparison of F-measures. CoRR abs/2112.04677 (2021) - 2020
- [j19]Yang Yu, Ning Zhang, Daniel W. Apley, Wenxin Jiang:
Including a Nugget Effect in Lifted Brownian Covariance Models. SIAM/ASA J. Uncertain. Quantification 8(4): 1338-1357 (2020) - [i3]Wenxin Jiang:
Statistical Formulas for F Measures. CoRR abs/2012.14894 (2020)
2010 – 2019
- 2019
- [i2]Ruimin Zhu, Thanapon Noraset, Alisa Liu, Wenxin Jiang, Doug Downey:
Multi-sense Definition Modeling using Word Sense Decompositions. CoRR abs/1909.09483 (2019) - 2018
- [j18]Phu Van, Wenxin Jiang, Raphael Gottardo, Greg Finak:
ggCyto: next generation open-source visualization software for cytometry. Bioinform. 34(22): 3951-3953 (2018) - [c14]Ruimin Zhu, Wenxin Jiang:
Bayesian Complex Network Community Detection Using Nonparametric Topic Model. COMPLEX NETWORKS (1) 2018: 280-291 - 2017
- [j17]Grace Yoon, Yinan Zheng, Zhou Zhang, Haixiang Zhang, Tao Gao, Brian Joyce, Wei Zhang, Weihua Guan, Andrea A. Baccarelli, Wenxin Jiang, Joel Schwartz, Pantel Vokonas, Lifang Hou, Lei Liu:
Ultra-high dimensional variable selection with application to normative aging study: DNA methylation and metabolic syndrome. BMC Bioinform. 18(1): 156:1-156:7 (2017) - 2016
- [j16]Yi Gao, Wenxin Jiang, Martin A. Tanner:
Generalized Gini Correlation and its Application in Data-Mining. Data Min. Knowl. Discov. 30(6): 1455-1479 (2016) - [j15]Cheng Li, Wenxin Jiang:
On oracle property and asymptotic validity of Bayesian generalized method of moments. J. Multivar. Anal. 145: 132-147 (2016) - 2014
- [j14]Greg Finak, Jacob Frelinger, Wenxin Jiang, Evan W. Newell, John Ramey, Mark M. Davis, Spyros A. Kalams, Stephen C. De Rosa, Raphael Gottardo:
OpenCyto: An Open Source Infrastructure for Scalable, Robust, Reproducible, and Automated, End-to-End Flow Cytometry Data Analysis. PLoS Comput. Biol. 10(8) (2014) - 2013
- [j13]Wenxin Jiang, Zbigniew W. Ras:
Multi-label automatic indexing of music by cascade classifiers. Web Intell. Agent Syst. 11(2): 149-170 (2013) - [c13]Cheng Li, Wenxin Jiang, Martin A. Tanner:
General Oracle Inequalities for Gibbs Posterior with Application to Ranking. COLT 2013: 512-521 - [i1]Wenxin Jiang, Martin A. Tanner:
Hierarchical Mixtures-of-Experts for Exponential Family Regression Models with Generalized Linear Mean Functions: A Survey of Approximation and Consistency Results. CoRR abs/1301.7390 (2013) - 2012
- [j12]Greg Finak, Wenxin Jiang, Jorge Pardo, Adam Asare, Raphael Gottardo:
QUAliFiER: An automated pipeline for quality assessment of gated flow cytometry data. BMC Bioinform. 13: 252 (2012) - [j11]Eduardo F. Mendes, Wenxin Jiang:
On Convergence Rates of Mixtures of Polynomial Experts. Neural Comput. 24(11): 3025-3051 (2012) - 2011
- [j10]Lili Yao, Wenxin Jiang, Martin A. Tanner:
Predicting Panel Data Binary Choice with the Gibbs Posterior. Neural Comput. 23(10): 2683-2712 (2011) - [c12]Bozena Kostek, Adam Kupryjanow, Pawel Zwan, Wenxin Jiang, Zbigniew W. Ras, Marcin Wojnarski, Joanna Swietlicka:
Report of the ISMIS 2011 Contest: Music Information Retrieval. ISMIS 2011: 715-724 - 2010
- [c11]Cynthia Xin Zhang, Wenxin Jiang, Zbigniew W. Ras, Rory A. Lewis:
Blind Music Timbre Source Isolation by Multi- resolution Comparison of Spectrum Signatures. RSCTC 2010: 610-619 - [p5]Wenxin Jiang, Zbigniew W. Ras, Alicja Wieczorkowska:
Clustering Driven Cascade Classifiers for Multi-indexing of Polyphonic Music by Instruments. Advances in Music Information Retrieval 2010: 19-38 - [p4]Zbigniew W. Ras, Agnieszka Dardzinska, Wenxin Jiang:
Cascade Classifiers for Hierarchical Decision Systems. Advances in Machine Learning I 2010: 247-256 - [p3]Wenxin Jiang, Cynthia Xin Zhang, Amanda Cohen, Zbigniew W. Ras:
Multiple Classifiers for Different Features in Timbre Estimation. Advances in Intelligent Information Systems 2010: 335-356
2000 – 2009
- 2009
- [j9]Wenxin Jiang:
On Uniform Deviations of General Empirical Risks with Unboundedness, Dependence, and High Dimensionality. J. Mach. Learn. Res. 10: 977-996 (2009) - [p2]Wenxin Jiang, Amanda Cohen, Zbigniew W. Ras:
Polyphonic Music Information Retrieval Based on Multi-label Cascade Classification System. Advances in Information and Intelligent Systems 2009: 117-137 - [p1]Wenxin Jiang, Alicja Wieczorkowska, Zbigniew W. Ras:
Music Instrument Estimation in Polyphonic Sound Based on Short-Term Spectrum Match. Foundations of Computational Intelligence (2) 2009: 259-273 - 2008
- [c10]Cynthia Xin Zhang, Wenxin Jiang, Zbigniew W. Ras:
Harmonic Blind Sound Source Isolation Enhanced by Spectrum Clustering. ICDM Workshops 2008: 310-319 - [c9]Rory A. Lewis, Wenxin Jiang, Zbigniew W. Ras:
Mining Scalar Representations in a Non-tagged Music Database. ISMIS 2008: 445-454 - [c8]Rory A. Lewis, Amanda Cohen, Wenxin Jiang, Zbigniew W. Ras:
Hierarchical Tree for Dissemination of Polyphonic Noise. RSCTC 2008: 448-456 - 2007
- [c7]Pamela L. Thompson, Cynthia Xin Zhang, Wenxin Jiang, Zbigniew W. Ras:
From Mining Tinnitus Database to Tinnitus Decision-Support System, Initial Study. IAT 2007: 203-206 - 2006
- [j8]Yang Ge, Wenxin Jiang:
On Consistency of Bayesian Inference with Mixtures of Logistic Regression. Neural Comput. 18(1): 224-243 (2006) - [j7]Wenxin Jiang:
On the Consistency of Bayesian Variable Selection for High Dimensional Binary Regression and Classification. Neural Comput. 18(11): 2762-2776 (2006) - [c6]Yang Ge, Wenxin Jiang:
A note on mixtures of experts for multiclass responses: approximation rate and Consistent Bayesian Inference. ICML 2006: 329-335 - 2004
- [j6]Wenxin Jiang:
Boosting with Noisy Data: Some Views from Statistical Theory. Neural Comput. 16(4): 789-810 (2004) - 2002
- [j5]Robert A. Jacobs, Wenxin Jiang, Martin A. Tanner:
Factorial Hidden Markov Models and the Generalized Backfitting Algorithm. Neural Comput. 14(10): 2415-2437 (2002) - 2001
- [c5]Wenxin Jiang:
Is regularization unnecessary for boosting?. AISTATS 2001 - [c4]Wenxin Jiang:
Some Theoretical Aspects of Boosting in the Presence of Noisy Data. ICML 2001: 234-241 - 2000
- [j4]Wenxin Jiang:
The VC Dimension for Mixtures of Binary Classifiers. Neural Comput. 12(6): 1293-1301 (2000) - [j3]Wenxin Jiang, Martin A. Tanner:
On the asymptotic normality of hierarchical mixtures-of-experts for generalized linear models. IEEE Trans. Inf. Theory 46(3): 1005-1013 (2000) - [c3]Wenxin Jiang:
Some Results on Weakly Accurate Base Learners for Boosting Regression and Classification. Multiple Classifier Systems 2000: 87-96
1990 – 1999
- 1999
- [j2]Wenxin Jiang, Martin A. Tanner:
On the Approximation Rate of Hierarchical Mixtures-of-Experts for Generalized Linear Models. Neural Comput. 11(5): 1183-1198 (1999) - [j1]Wenxin Jiang, Martin A. Tanner:
On the identifiability of mixtures-of-experts. Neural Networks 12(9): 1253-1258 (1999) - [c2]Wenxin Jiang, Martin A. Tanner:
Hierarchical mixtures-of-experts for generalized linear models: some results on denseness and consistency. AISTATS 1999 - 1998
- [c1]Wenxin Jiang, Martin A. Tanner:
Hierarchical Mixtures-of-Experts for Exponential Family Regression Models with Generalized Linear Mean Functions: A Survey of Approximation and Consistency Results. UAI 1998: 296-303
Coauthor Index
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