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@misc{zhouchizhou2023,
author = {Zhou, Xinkai and Heng, Qiang and Chi, Eric C. and Zhou, Hua},
title = {Proximal MCMC for Bayesian Inference of Constrained and Regularized Estimation},
journal = {The American Statistician},
group = {publications},
volume = {78},
number = {4},
pages = {379--390},
year = {2024},
arxiv = {https://arxiv.org/abs/2205.07378},
link = {https://www.tandfonline.com/doi/full/10.1080/00031305.2024.2308821},
pdf = {https://arxiv.org/pdf/2205.07378.pdf}
}
Liu, X., Han, X., Chi, E. C. and Nadler, B. (2024). A Majorization-Minimization Gauss-Newton Method for 1-Bit Matrix Completion. Journal of Computational and Graphical Statistics, In press. arXiv:2304.13940 [stat.ML].
@misc{liuhanchinadler2023,
title = {A Majorization-Minimization Gauss-Newton Method for 1-Bit Matrix Completion},
author = {Liu, Xiaoqian and Han, Xu and Chi, Eric C. and Nadler, Boaz},
group = {publications},
year = {2024},
journal = {Journal of Computational and Graphical Statistics, In press},
arxiv = {https://arxiv.org/abs/2304.13940},
pdf = {https://arxiv.org/pdf/2304.13940.pdf},
howpublished = {arXiv:2304.13940 [stat.ML]}
}
Qiang Heng, H. Z. and Chi, E. C. (2023). Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo. Journal of Computational and Graphical Statistics, 32(3), 938–949. doi:10.1080/10618600.2023.2170089
@article{hengzhouchi2023,
author = {Qiang Heng, Hua Zhou and Chi, Eric C.},
title = {Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo},
journal = {Journal of Computational and Graphical Statistics},
volume = {32},
number = {3},
pages = {938-949},
year = {2023},
publisher = {Taylor & Francis},
doi = {10.1080/10618600.2023.2170089},
note = {PMID: 37822489},
link = {https://doi.org/10.1080/10618600.2023.2170089},
arxiv = {https://arxiv.org/abs/2201.00092},
pdf = {https://arxiv.org/pdf/2201.00092.pdf},
group = {publications}
}
Liu, X., Molstad, A. J. and Chi, E. C. (2023). A convex-nonconvex strategy for grouped variable selection. Electronic Journal of Statistics, 17(2), 2912–2961. doi:10.1214/23-EJS2167
@article{liumolstadchi2023,
author = {Liu, Xiaoqian and Molstad, Aaron J. and Chi, Eric C.},
title = {{A convex-nonconvex strategy for grouped variable selection}},
volume = {17},
journal = {Electronic Journal of Statistics},
number = {2},
publisher = {Institute of Mathematical Statistics and Bernoulli Society},
pages = {2912 -- 2961},
keywords = {Convex optimization, convex-nonconvex penalization, high-dimensional data analysis, sparse linear regression},
year = {2023},
doi = {10.1214/23-EJS2167},
url = {https://doi.org/10.1214/23-EJS2167},
group = {publications},
pdf = {https://arxiv.org/pdf/2111.15075.pdf},
arxiv = {https://arxiv.org/abs/2111.15075}
}
Qiang Heng, E. C. C. and Liu, Y. (2023). Robust Low-Rank Tensor Decomposition with the L2 Criterion. Technometrics, 65(4), 537–552. doi:10.1080/00401706.2023.2200541
@article{hengchiliu2023,
author = {Qiang Heng, Eric C. Chi and Liu, Yufeng},
title = {Robust Low-Rank Tensor Decomposition with the L2 Criterion},
journal = {Technometrics},
volume = {65},
number = {4},
pages = {537-552},
year = {2023},
publisher = {Taylor & Francis},
doi = {10.1080/00401706.2023.2200541},
link = {https://doi.org/10.1080/00401706.2023.2200541},
arxiv = {https://arxiv.org/abs/2208.11806},
pdf = {https://arxiv.org/pdf/2208.11806.pdf},
group = {publications}
}
Chi, J. T. and Chi, E. C. (2022). A User-Friendly Computational Framework for Robust Structured Regression with the L_2 Criterion. Journal of Computational and Graphical Statistics, 31(4), 1051–1062. doi:10.1080/10618600.2022.2035232
@article{l2e,
author = {Chi, Jocelyn T. and Chi, Eric C.},
title = {A User-Friendly Computational Framework for Robust Structured Regression with the L$_2$ Criterion},
year = {2022},
group = {publications},
arxiv = {https://arxiv.org/abs/2010.04133},
journal = {Journal of Computational and Graphical Statistics},
volume = {31},
number = {4},
pages = {1051-1062},
publisher = {Taylor & Francis},
doi = {10.1080/10618600.2022.2035232},
pdf = {https://arxiv.org/pdf/2010.04133.pdf},
code = {https://jocelynchi.github.io/L2E-package-demo/},
link = {https://amstat.tandfonline.com/doi/full/10.1080/10618600.2022.2035232#.Yfr47S-B0Ts}
}
Zhang, M., Mishne, G. and Chi, E. C. (2022). Multi-scale Affinities with Missing Data: Estimation and Applications. Statistical Analysis and Data Mining, 15(3), 303–313. doi:10.1002/sam.11561
@article{Zhang2021,
author = {Zhang, Min and Mishne, Gal and Chi, Eric C.},
journal = {Statistical Analysis and Data Mining},
title = {Multi-scale Affinities with Missing Data: Estimation and Applications},
year = {2022},
volume = {15},
number = {3},
pages = {303-313},
link = {https://onlinelibrary.wiley.com/doi/10.1002/sam.11561},
doi = {10.1002/sam.11561},
group = {publications}
}
Liu, X. and Chi, E. C. (2022). Revisiting convexity-preserving signal recovery with the linearly involved GMC penalty. Pattern Recognition Letters, 156, 60–66. doi:https://doi.org/10.1016/j.patrec.2022.02.004
@article{LIU202260,
author = {Liu, Xiaoqian and Chi, Eric C.},
doi = {https://doi.org/10.1016/j.patrec.2022.02.004},
issn = {0167-8655},
journal = {Pattern Recognition Letters},
pages = {60-66},
title = {Revisiting convexity-preserving signal recovery with the linearly involved GMC penalty},
link = {https://www.sciencedirect.com/science/article/pii/S0167865522000381},
volume = {156},
year = {2022},
group = {publications}
}
Zhou, W., Yi, H., Mishne, G. and Chi, E. C. (2021). Scalable Algorithms for Convex Clustering. Proceedings of the 2021 IEEE Data Science and Learning Workshop (DSLW 2021), 1–6. doi:10.1109/DSLW51110.2021.9523411
@article{ZhouYiMishneChi2021,
title = {Scalable Algorithms for Convex Clustering},
author = {Zhou, Weilian and Yi, Haidong and Mishne, Gal and Chi, Eric C.},
journal = {Proceedings of the 2021 IEEE Data Science and Learning Workshop (DSLW 2021)},
year = {2021},
address = {Toronto, ON, Canada},
month = jun,
pages = {1--6},
doi = {10.1109/DSLW51110.2021.9523411},
group = {publications}
}
Liu, X., Vardhan, M., Wen, Q., Das, A., Randles, A. and Chi, E. C. (2021). An Interpretable Machine Learning Model to Classify Coronary Bifurcation Lesions. Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).
@article{Liu2022,
title = {An Interpretable Machine Learning Model to Classify Coronary Bifurcation Lesions},
author = {Liu, Xiaoqian and Vardhan, Madhurima and Wen, Qinrou and Das, Arpita and Randles, Amanda and Chi, Eric C.},
journal = {Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)},
year = {2021},
address = {Guadalajara, Mexico},
month = jun,
group = {publications}
}
Yi, H., Huang, L., Mishne, G. and Chi, E. C. (2021). COBRAC: A fast implementation of convex biclustering with compression. Bioinformatics. doi:10.1093/bioinformatics/btab248
@article{cobrac,
author = {Yi, Haidong and Huang, Le and Mishne, Gal and Chi, Eric C.},
title = {COBRAC: A fast implementation of convex biclustering with compression},
journal = {Bioinformatics},
year = {2021},
month = apr,
code = {https://cvxbiclustr.rice.edu},
issn = {1367-4803},
doi = {10.1093/bioinformatics/btab248},
link = {https://doi.org/10.1093/bioinformatics/btab248},
pdf = {https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btab248/37414425/btab248.pdf},
group = {publications}
}
Chi, E. C. (2021). Discovering Geometry in Data Arrays. Computing in Science and Engineering, 23(6), 42–51. doi:10.1109/MCSE.2021.3120039
@article{chicse2021,
author = {Chi, Eric C.},
journal = {Computing in Science and Engineering},
title = {Discovering Geometry in Data Arrays},
year = {2021},
volume = {23},
number = {6},
pages = {42-51},
group = {publications},
doi = {10.1109/MCSE.2021.3120039}
}
Vardhan, M., Gounley, J., Chen, S. J., Chi, E. C., Kahn, A. M., Leopold, J. A. and Randles, A. (2021). Non-invasive characterization of complex coronary lesions. Nature Scientific Reports, 11(1), 8145. doi:10.1038/s41598-021-86360-6
@article{Vardhan2021,
author = {Vardhan, Madhurima and Gounley, John and Chen, S. James and Chi, Eric C. and Kahn, Andrew M. and Leopold, Jane A. and Randles, Amanda},
doi = {10.1038/s41598-021-86360-6},
journal = {Nature Scientific Reports},
number = {1},
pages = {8145},
group = {publications},
title = {Non-invasive characterization of complex coronary lesions},
link = {https://doi.org/10.1038/s41598-021-86360-6},
volume = {11},
year = {2021}
}
Feng, Y., Xiao, L. and Chi, E. C. (2021). Sparse Single Index Models for Multivariate Responses. Journal of Computational and Graphical Statistics, 30(1), 115–124. doi:10.1080/10618600.2020.1779080
@article{FengXiaoChi2020,
author = {Feng, Y. and Xiao, L. and Chi, E. C.},
title = {{Sparse Single Index Models for Multivariate Responses}},
journal = {Journal of Computational and Graphical Statistics},
volume = {30},
number = {1},
pages = {115-124},
year = {2021},
group = {publications},
link = {https://doi.org/10.1080/10618600.2020.1779080},
doi = {10.1080/10618600.2020.1779080}
}
Brantley, H. L., Guinness, J. and Chi, E. C. (2020). Baseline drift estimation for air quality data using quantile trend filtering. The Annals of Applied Statistics, 14(2), 585–604. doi:10.1214/19-AOAS1318
@article{BraGuiChi2019,
author = {Brantley, Halley L. and Guinness, Joseph and Chi, Eric C.},
doi = {10.1214/19-AOAS1318},
journal = {The Annals of Applied Statistics},
month = jun,
number = {2},
pages = {585--604},
publisher = {The Institute of Mathematical Statistics},
title = {Baseline drift estimation for air quality data using quantile trend filtering},
link = {https://doi.org/10.1214/19-AOAS1318},
volume = {14},
year = {2020},
pdf = {http://ericchi.com/ec_papers/AOAS1318.pdf},
group = {publications}
}
Rhyne, J., Jeng, X. J., Chi, E. C. and Tzeng, J.-Y. (2020). FastLORS: Joint modelling for expression quantitative trait loci mapping in R. Stat, 9(1), e265. doi:10.1002/sta4.265
@article{RhyChiTzeJen2019,
author = {Rhyne, Jacob and Jeng, X. Jessie and Chi, Eric C. and Tzeng, Jung-Ying},
title = {FastLORS: Joint modelling for expression quantitative trait loci mapping in R},
journal = {Stat},
volume = {9},
number = {1},
pages = {e265},
keywords = {block coordinate descent, eQTL mapping, low-rank approximation, proximal gradient descent, sparse regression},
doi = {10.1002/sta4.265},
link = {https://onlinelibrary.wiley.com/doi/abs/10.1002/sta4.265},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/sta4.265},
note = {e265 sta4.265},
year = {2020},
group = {publications}
}
Chi, E. C., Gaines, B. J., Sun, W. W., Zhou, H. and Yang, J. (2020). Provable Convex Co-clustering of Tensors. Journal of Machine Learning Research, 21(214), 1–58.
@article{JMLRv2118155,
author = {Chi, Eric C. and Gaines, Brian J. and Sun, Will Wei and Zhou, Hua and Yang, Jian},
title = {Provable Convex Co-clustering of Tensors},
journal = {Journal of Machine Learning Research},
year = {2020},
volume = {21},
number = {214},
pages = {1-58},
link = {http://jmlr.org/papers/v21/18-155.html},
group = {publications}
}
Stanley III, J. S., Chi, E. C. and Mishne, G. (2020). Multiway Graph Signal Processing on Tensors: Integrative Analysis of Irregular Geometries. IEEE Signal Processing Magazine, 37(6), 160–173. doi:10.1109/MSP.2020.3013555
@article{StanleyChiMishne2020,
author = {{Stanley III}, J. S. and {Chi}, E. C. and {Mishne}, G.},
journal = {IEEE Signal Processing Magazine},
title = {Multiway Graph Signal Processing on Tensors: Integrative Analysis of Irregular Geometries},
year = {2020},
volume = {37},
number = {6},
pages = {160-173},
doi = {10.1109/MSP.2020.3013555},
group = {publications}
}
Chi, E. C. and Li, T. (2019). Matrix Completion from a Computational Statistics Perspective. WIREs Computational Statistics, e1469. doi:10.1002/wics.1469
@article{chili2019,
author = {Chi, Eric C. and Li, Tianxi},
title = {Matrix Completion from a Computational Statistics Perspective},
journal = {WIREs Computational Statistics},
pages = {e1469},
doi = {10.1002/wics.1469},
link = {https://onlinelibrary.wiley.com/doi/abs/10.1002/wics.1469},
year = {2019},
group = {publications}
}
Chi, E. and Steinerberger, S. (2019). Recovering Trees with Convex Clustering. SIAM Journal on Mathematics of Data Science, 1(3), 383–407. doi:10.1137/18M121099X
@article{ChiSte2018,
author = {Chi, E. and Steinerberger, S.},
title = {Recovering Trees with Convex Clustering},
journal = {SIAM Journal on Mathematics of Data Science},
volume = {1},
number = {3},
pages = {383-407},
year = {2019},
doi = {10.1137/18M121099X},
link = {https://doi.org/10.1137/18M121099X},
pdf = {http://www.ericchi.com/ec_papers/ChiSteinerberger2019.pdf},
group = {publications}
}
Mishne, G., Chi, E. C. and Coifman, R. R. (2019). Co-manifold learning with missing data. K. Chaudhuri and R. Salakhutdinov (Eds.), Proceedings of the 36th International Conference on Machine Learning in , Proceedings of Machine Learning Research (Vol. 97, pp. 4605–4614). Long Beach, California, USA: PMLR.
@inproceedings{michenechicoifmanicml,
title = {Co-manifold learning with missing data},
author = {Mishne, Gal and Chi, Eric C. and Coifman, Ronald R.},
booktitle = {Proceedings of the 36th International Conference on Machine Learning},
pages = {4605--4614},
year = {2019},
editor = {Chaudhuri, Kamalika and Salakhutdinov, Ruslan},
volume = {97},
series = {Proceedings of Machine Learning Research},
address = {Long Beach, California, USA},
month = {09--15 Jun},
publisher = {PMLR},
link = {http://proceedings.mlr.press/v97/mishne19a.html},
group = {publications},
pdf = {https://arxiv.org/pdf/1810.06803.pdf}
}
Min, E. J., Chi, E. C. and Zhou, H. (2019). Tensor Canonical Correlation Analysis. Stat, 8(1), e253. doi:10.1002/sta4.253
@article{minchizhou2019,
author = {Min, Eun Jeong and Chi, Eric C. and Zhou, Hua},
title = {Tensor Canonical Correlation Analysis},
journal = {Stat},
year = {2019},
volume = {8},
number = {1},
pages = {e253},
doi = {10.1002/sta4.253},
group = {publications}
}
Lusch, B., Chi, E. C. and Kutz, J. N. (2019). Shape Constrained Tensor Decompositions. 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA) in (pp. 287–297). doi:10.1109/DSAA.2019.00044
@inproceedings{LuschChiKutz2019,
author = {Lusch, Bethany and Chi, Eric C. and Kutz, J. Nathan},
title = {Shape Constrained Tensor Decompositions},
booktitle = {2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA)},
year = {2019},
pages = {287-297},
group = {publications},
doi = {10.1109/DSAA.2019.00044}
}
Chi, E. C., Hu, L., Saibaba, A. K. and Rao, A. U. K. (2019). Going Off the Grid: Iterative Model Selection for Biclustered Matrix Completion. Journal of Computational and Graphical Statistics, 28(1), 36–47. doi:10.1080/10618600.2018.1482763
@article{ChiHuSaiRao2018,
author = {Chi, Eric C. and Hu, Liuyi and Saibaba, Arvind K. and Rao, Arvind U. K.},
title = {Going Off the Grid: Iterative Model Selection for Biclustered Matrix Completion},
journal = {Journal of Computational and Graphical Statistics},
volume = {28},
number = {1},
pages = {36-47},
year = {2019},
publisher = {Taylor & Francis},
doi = {10.1080/10618600.2018.1482763},
link = {https://doi.org/10.1080/10618600.2018.1482763},
group = {publications}
}
Xu, J., Chi, E. C., Yang, M. and Lange, K. (2018). A Majorization-Minimization Algorithm for Split Feasibility Problems. Computational Optimization and Applications, 71(3), 795–828. doi:doi:10.1007/s10589-018-0025-z
@article{XuChiYanLan2018,
author = {Xu, Jason and Chi, Eric C. and Yang, Meng and Lange, Kenneth},
title = {A Majorization-Minimization Algorithm for Split Feasibility Problems},
journal = {Computational Optimization and Applications},
year = {2018},
volume = {71},
number = {3},
pages = {795--828},
link = {https://doi.org/10.1007/s10589-018-0025-z},
doi = {doi:10.1007/s10589-018-0025-z},
group = {publications}
}
Xu, J., Chi, E. C. and Lange, K. (2017). Generalized Linear Model Regression under Distance-to-set Penalties. I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan and R. Garnett (Eds.), Advances in Neural Information Processing Systems 30 in (pp. 1385–1395). Curran Associates, Inc.
@inproceedings{XuChiLan2017,
title = {Generalized Linear Model Regression under Distance-to-set Penalties},
author = {Xu, Jason and Chi, Eric C. and Lange, Kenneth},
booktitle = {Advances in Neural Information Processing Systems 30},
editor = {Guyon, I. and Luxburg, U. V. and Bengio, S. and Wallach, H. and Fergus, R. and Vishwanathan, S. and Garnett, R.},
pages = {1385--1395},
year = {2017},
publisher = {Curran Associates, Inc.},
pdf = {http://papers.nips.cc/paper/6737-generalized-linear-model-regression-under-distance-to-set-penalties.pdf},
group = {publications}
}
Chi, E. C., Allen, G. I. and Baraniuk, R. G. (2017). Convex Biclustering. Biometrics, 73(1), 10–19. doi:10.1111/biom.12540
@article{ChiAllBar2017,
title = {Convex Biclustering},
author = {Chi, Eric C. and Allen, Genevera I. and Baraniuk, Richard G.},
journal = {Biometrics},
year = {2017},
volume = {73},
number = {1},
pages = {10--19},
doi = {10.1111/biom.12540},
link = {http://dx.doi.org/10.1111/biom.12540},
group = {publications}
}
Long, J. P., Chi, E. C. and Baraniuk, R. G. (2016). Estimating a common period for a set of irregularly sampled functions with applications to periodic variable star data. The Annals of Applied Statistics, 10(1), 165–197. doi:10.1214/15-AOAS885
@article{LonChiBar2016,
author = {Long, James P. and Chi, Eric C. and Baraniuk, Richard G.},
doi = {10.1214/15-AOAS885},
journal = {The Annals of Applied Statistics},
month = mar,
number = {1},
pages = {165--197},
publisher = {The Institute of Mathematical Statistics},
title = {Estimating a common period for a set of irregularly sampled functions with applications to periodic variable star data},
link = {http://dx.doi.org/10.1214/15-AOAS885},
volume = {10},
year = {2016},
group = {publications},
code = {http://cran.r-project.org/web/packages/multiband/index.html},
pdf = {http://ericchi.com/ec_papers/euclid.aoas.1458909912.pdf}
}
Chi, J. T., Chi, E. C. and Baraniuk, R. G. (2016). k-POD: A Method for k-Means Clustering of Missing Data. The American Statistician, 70(1), 91–99. doi:10.1080/00031305.2015.1086685
@article{ChiChiBar2016,
author = {Chi, Jocelyn T. and Chi, Eric C. and Baraniuk, Richard G.},
title = {$k$-POD: A Method for $k$-Means Clustering of Missing Data},
journal = {The American Statistician},
year = {2016},
volume = {70},
pages = {91-99},
link = {http://www.tandfonline.com/doi/abs/10.1080/00031305.2015.1086685},
pdf = {http://www.tandfonline.com/doi/pdf/10.1080/00031305.2015.1086685},
doi = {10.1080/00031305.2015.1086685},
issue = {1},
group = {publications},
code = {http://jocelynchi.com/kpodclustr}
}
Chi, E. C., Zhou, H., Chen, G. K., Ortega-Del-Vecchyo, D. and Lange, K. (2015). Genotype Imputation via Matrix Completion. Genome Research. doi:10.1101/gr.145821.112
@article{ChiZhoChe2013,
author = {Chi, Eric C. and Zhou, Hua and Chen, Gary K. and Ortega-Del-Vecchyo, Diego and Lange, Kenneth},
title = {Genotype Imputation via Matrix Completion},
journal = {Genome Research},
doi = {10.1101/gr.145821.112},
code = {https://www.genetics.ucla.edu/software/},
group = {publications},
year = {2015}
}
Chi, E. C. and Lange, K. (2015). Splitting Methods for Convex Clustering. Journal of Computational and Graphical Statistics, 24(4), 994–1013. doi:10.1080/10618600.2014.948181
@article{ChiLan2015,
author = {Chi, Eric C. and Lange, Kenneth},
title = {Splitting Methods for Convex Clustering},
journal = {Journal of Computational and Graphical Statistics},
year = {2015},
volume = {24},
pages = {994-1013},
number = {4},
doi = {10.1080/10618600.2014.948181},
link = {http://dx.doi.org/10.1080/10618600.2014.948181},
group = {publications},
pdf = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4830509/pdf/nihms746782.pdf},
code = {http://cran.r-project.org/web/packages/cvxclustr/index.html}
}
Chen, G. K., Chi, E. C., Ranola, J. M. O. and Lange, K. (2015). Convex Clustering: An Attractive Alternative to Hierarchical Clustering. PLoS Computational Biology, 11(5), e1004228. doi:10.1371/journal.pcbi.1004228
@article{CheChiRan2015,
author = {Chen, Gary K. and Chi, Eric C. and Ranola, John M.O. and Lange, Kenneth},
title = {Convex Clustering: An Attractive Alternative to Hierarchical Clustering},
journal = {PLoS Computational Biology},
year = {2015},
volume = {11},
pages = {e1004228},
number = {5},
doi = {10.1371/journal.pcbi.1004228},
link = {http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004228},
pdf = {http://www.ericchi.com/ec_papers/journal.pcbi.1004228.pdf},
group = {publications},
code = {https://code.google.com/p/proxmap-mm/}
}
Chi, E. C. and Lange, K. (2014). Stable Estimation of a Covariance Matrix Guided by Nuclear Norm Penalties. Computational Statistics & Data Analysis, 80(0), 117–128. doi:10.1016/j.csda.2014.06.018
@article{ChiLan2014,
author = {Chi, Eric C. and Lange, Kenneth},
title = {Stable Estimation of a Covariance Matrix Guided by Nuclear Norm Penalties},
journal = {Computational Statistics \& Data Analysis},
year = {2014},
volume = {80},
number = {0},
pages = {117-128},
doi = {10.1016/j.csda.2014.06.018},
group = {publications},
code = {http://cran.r-project.org/web/packages/cernn/index.html}
}
Lange, K., Chi, E. C. and Zhou, H. (2014). A brief survey of optimization for statisticians: Rejoinder. International Statistical Review, 82(1), 81–89. doi:10.1111/insr.12030
@article{LanChiZho2014_rejoinder,
author = {Lange, Kenneth and Chi, Eric C. and Zhou, Hua},
title = {A brief survey of optimization for statisticians: Rejoinder},
journal = {International Statistical Review},
year = {2014},
volume = {82},
number = {1},
pages = {81-89},
doi = {10.1111/insr.12030},
link = {http://dx.doi.org/10.1111/insr.12030},
group = {publications}
}
Chi, E. C. and Scott, D. W. (2014). Robust Parametric Classification and Variable Selection by a Minimum Distance Criterion. Journal of Computational and Graphical Statistics, 23(1), 111–128. doi:10.1080/10618600.2012.737296
@article{ChiSco2013,
author = {Chi, Eric C. and Scott, David W.},
title = {Robust Parametric Classification and Variable Selection by a Minimum Distance Criterion},
journal = {Journal of Computational and Graphical Statistics},
year = {2014},
volume = {23},
number = {1},
pages = {111-128},
doi = {10.1080/10618600.2012.737296},
link = {http://amstat.tandfonline.com/doi/full/10.1080/10618600.2012.737296},
group = {publications}
}
Chi, E. C. and Lange, K. (2014). A Look at the Generalized Heron Problem through the Lens of Majorization-Minimization. The American Mathematical Monthly, 121(2), 95–108. doi:10.4169/amer.math.monthly.121.02.095
@article{ChiLan2016,
author = {Chi, Eric C. and Lange, Kenneth},
title = {A Look at the Generalized Heron Problem through the Lens of Majorization-Minimization},
journal = {The American Mathematical Monthly},
year = {2014},
volume = {121},
number = {2},
pages = {95-108},
doi = {10.4169/amer.math.monthly.121.02.095},
link = {http://dx.doi.org/10.4169/amer.math.monthly.121.02.095},
pdf = {http://www.ericchi.com/ec_papers/amer.math.monthly.121.02.095-chi.pdf},
note = {This article was translated into Chinese and appeared in Mathematical Advances in Translation, vol. 34, pp. 221--232, 2015.},
group = {publications}
}
Chi, E. C., Zhou, H. and Lange, K. (2014). Distance Majorization and Its Applications. Mathematical Programming Series A, 146(1-2), 409–436. doi:10.1007/s10107-013-0697-1
@article{1211.3907v5,
author = {Chi, Eric C. and Zhou, Hua and Lange, Kenneth},
title = {Distance Majorization and Its Applications},
journal = {Mathematical Programming Series A},
year = {2014},
volume = {146},
number = {1-2},
pages = {409-436},
doi = {10.1007/s10107-013-0697-1},
group = {publications}
}
Lange, K., Chi, E. C. and Zhou, H. (2014). A brief survey of optimization for statisticians. International Statistical Review, 82(1), 46–70. doi:10.1111/insr.12022
@article{LanChiZho2014,
author = {Lange, Kenneth and Chi, Eric C. and Zhou, Hua},
title = {A brief survey of optimization for statisticians},
journal = {International Statistical Review},
year = {2014},
volume = {82},
number = {1},
pages = {46-70},
doi = {10.1111/insr.12022},
group = {publications}
}
Chi, E. C., Allen, G. I., Zhou, H., Kohannim, O., Lange, K. and Thompson, P. M. (2013). Imaging genetics via sparse canonical correlation analysis. Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on in (pp. 740–743). doi:10.1109/ISBI.2013.6556581
@inproceedings{chiisbi2013,
author = {Chi, Eric C. and Allen, Genevera I. and Zhou, Hua and Kohannim, Omid and Lange, Kenneth and Thompson, Paul M.},
title = {Imaging genetics via sparse canonical correlation analysis},
booktitle = {Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on},
year = {2013},
pages = {740-743},
keywords = {Bioinformatics;Biomedical imaging;Correlation;Covariance matrices;Genomics;Canonical correlation analysis;Diffusion tensor imaging;Genome wide association;lasso;sparsity},
doi = {10.1109/ISBI.2013.6556581},
group = {publications},
pdf = {http://www.ericchi.com/ec_papers/chi_spCCA.pdf}
}
Chi, E. C. and Kolda, T. G. (2012). On Tensors, Sparsity, and Nonnegative Factorizations. SIAM Journal on Matrix Analysis and Applications, 33(4), 1272–1299. doi:10.1137/110859063
@article{ChiKol2012,
author = {Chi, Eric C. and Kolda, Tamara G.},
title = {On Tensors, Sparsity, and Nonnegative Factorizations},
journal = {SIAM Journal on Matrix Analysis and Applications},
year = {2012},
volume = {33},
pages = {1272--1299},
number = {4},
doi = {10.1137/110859063},
pdf = {http://www.ericchi.com/ec_papers/chi2011.pdf},
link = {http://epubs.siam.org/doi/pdf/10.1137/110859063},
group = {publications},
code = {http://www.sandia.gov/~tgkolda/TensorToolbox/index-2.5.html}
}
Chi, E. C., Mende, S. B., Fok, M.-C. and Reeves, G. D. (2006). Proton auroral intensifications and injections at synchronous altitude. Geophysical Research Letters, 33, 6104. doi:10.1029/2005GL024656
@article{Chi2006,
author = {Chi, Eric C. and Mende, Stephen B. and Fok, Mei-Ching and Reeves, Geoffrey D.},
title = {Proton auroral intensifications and injections at synchronous altitude},
journal = {Geophysical Research Letters},
year = {2006},
volume = {33},
pages = {6104},
month = mar,
adsnote = {Provided by the SAO/NASA Astrophysics Data System},
link = {http://adsabs.harvard.edu/abs/2006GeoRL..3306104C},
doi = {10.1029/2005GL024656},
keywords = {Magnetospheric Physics: Magnetospheric configuration and dynamics, Magnetospheric Physics: Substorms, Magnetospheric Physics: Auroral phenomena (2407), Magnetospheric Physics: Energetic particles: precipitating, Magnetospheric Physics: Energetic particles: trapped},
group = {publications},
pdf = {http://www.ericchi.com/ec_papers/chi2006.pdf}
}
Gupta, R., Chi, E. and Walrand, J. (2005). Different Algorithms for Normal and Protection Paths. Journal of Network System Management, 13(1), 13–33. doi:10.1007/s10922-005-1845-6
@article{GupChiWal2005,
author = {Gupta, Rajarshi and Chi, Eric and Walrand, Jean},
title = {Different Algorithms for Normal and Protection Paths.},
journal = {Journal of Network System Management},
year = {2005},
volume = {13},
pages = {13-33},
number = {1},
doi = {10.1007/s10922-005-1845-6},
pdf = {http://www.ericchi.com/ec_papers/gupta2005.pdf},
link = {http://dx.doi.org/10.1007/s10922-005-1845-6},
group = {publications}
}
Chi, E., Fu, M. and Walrand, J. (2004). Proactive resource provisioning. Computer Communications, 27(12), 1174–1182. doi:10.1016/j.comcom.2004.02.019
@article{ChiFuWal2004,
author = {Chi, Eric and Fu, Michael and Walrand, Jean},
title = {Proactive resource provisioning},
journal = {Computer Communications},
year = {2004},
volume = {27},
pages = {1174-1182},
number = {12},
doi = {10.1016/j.comcom.2004.02.019},
pdf = {http://www.ericchi.com/ec_papers/chi2004.pdf},
group = {publications}
}
Gupta, R., Chi, E. and Walrand, J. (2004). Sharing Normal Bandwidth During a Failure. Proceedings Seventh INFORMS Telecommunications Conference, Boca Raton, Florida in .
@conference{rguptamarch2004,
author = {Gupta, Rajarshi and Chi, Eric and Walrand, Jean},
title = {Sharing Normal Bandwidth During a Failure},
booktitle = {Proceedings Seventh INFORMS Telecommunications Conference, Boca Raton, Florida},
year = {2004},
journal = {Proceedings Seventh INFORMS Telecommunications Conference},
group = {publications},
pdf = {http://www.ericchi.com/ec_papers/rguptamarch2004.pdf}
}
Chi, E., Fu, M. and Walrand, J. (2003). Proactive Resource Provisioning for Voice over IP. Proceedings SPECTS 2003, Montreal, Canada in . doi:10.1.1.69.4215
@conference{echijuly2003,
author = {Chi, Eric and Fu, Michael and Walrand, Jean},
title = {Proactive Resource Provisioning for Voice over IP},
booktitle = {Proceedings SPECTS 2003, Montreal, Canada},
year = {2003},
doi = {10.1.1.69.4215},
journal = {Proceedings SPECTS 2003, Montreal, Canada},
group = {publications},
pdf = {http://www.ericchi.com/ec_papers/echijuly2003.pdf}
}
Gupta, R., Chi, E. and Walrand, J. (2003). Different Algorithms for Normal and Protection Paths, Banff, Canada. Proceedings DRCN 2003 in . doi:10.1109/DRCN.2003.1275356
@conference{rguptaoctober2003,
author = {Gupta, Rajarshi and Chi, Eric and Walrand, Jean},
title = {Different Algorithms for Normal and Protection Paths, Banff, Canada},
booktitle = {Proceedings DRCN 2003},
year = {2003},
doi = {10.1109/DRCN.2003.1275356},
group = {publications},
pdf = {http://www.ericchi.com/ec_papers/rguptaoctober2003.pdf}
}
Thomsen, S. L., Baldwin, B., Chi, E., Ellard, J. and Schwartz, J. A. (1997). Histopathology of laser skin resurfacing. Proceedings of SPIE Vol 2970 in . doi:10.1117/12.275056
@conference{sthomsenmay1997,
author = {Thomsen, Sharon L. and Baldwin, Bonnie and Chi, Eric and Ellard, Jeff and Schwartz, Jon A.},
title = {Histopathology of laser skin resurfacing},
booktitle = {Proceedings of SPIE Vol 2970},
year = {1997},
doi = {10.1117/12.275056},
pdf = {http://www.ericchi.com/ec_papers/287_1.pdf},
journal = {Proceedings of SPIE Vol 2970},
group = {publications}
}
Refereed Book Chapters and Other Refereed Articles
Chi, E. C. (2018). Proximal Methods for Penalized Regression. doi:10.1002/9781118445112.stat08052
@inbook{Chi2018,
author = {Chi, Eric C.},
title = {Proximal Methods for Penalized Regression},
book = {Wiley StatsRef-Statistics Reference Online},
doi = {10.1002/9781118445112.stat08052},
group = {refereed},
year = {2018}
}
Hu, Y., Chi, E. C. and Allen, G. I. (2016). Splitting Methods in Communication and Imaging, Science and Engineering. W. Y. S. Osher and R. Glowinski (Eds.), . Springer. doi:doi:10.1007/978-3-319-41589-5
@inbook{HuChiAll2016,
chapter = {ADMM Algorithmic Regularization Paths for Sparse Statistical Machine
Learning},
title = {Splitting Methods in Communication and Imaging, Science and Engineering},
publisher = {Springer},
editor = {S. Osher, W. Yin and Glowinski, R.},
year = {2016},
doi = {doi:10.1007/978-3-319-41589-5},
author = {Hu, Yue and Chi, Eric C. and Allen, Genevera I.},
group = {refereed}
}
Technical Reports and Other Papers
Chi, E. C. and Lange, K. (2012, March). Techniques for Solving Sudoku Puzzles. arXiv:1203.2295v3 [math.OC].
@misc{1203.2295v1,
author = {Chi, Eric C. and Lange, Kenneth},
title = {Techniques for Solving Sudoku Puzzles},
howpublished = {arXiv:1203.2295v3 [math.OC]},
month = mar,
year = {2012},
link = {http://arxiv.org/abs/1203.2295},
arxiv = {http://arxiv.org/abs/1203.2295},
group = {techreport}
}
Chi, E. C. and Kolda, T. G. (2011). Making Tensor Factorizations Robust to Non-Gaussian Noise ( No: SAND2011-1877). Sandia National Laboratories, Albuquerque, NM and Livermore, CA.
@techreport{sand2011-1877,
author = {Chi, Eric C. and Kolda, Tamara G.},
title = {Making Tensor Factorizations Robust to Non-Gaussian Noise},
institution = {Sandia National Laboratories, Albuquerque, NM and Livermore, CA},
year = {2011},
number = {SAND2011-1877},
month = mar,
pdf = {http://www.ericchi.com/ec_papers/sand2011-1877.pdf},
group = {techreport}
}
Chi, E. C. and Kolda, T. G. (2010, October). Making Tensor Factorizations Robust to Non-Gaussian Noise (Contributed paper at the NIPS Workshop on Tensors, Kernels, and Machine Learning, Whistler, BC, Canada, December 10, 2010). arXiv:1010.3043.
@misc{1010.3043v1,
author = {Chi, Eric C. and Kolda, Tamara G.},
title = {Making Tensor Factorizations Robust to Non-{G}aussian Noise (Contributed paper at the NIPS Workshop on Tensors, Kernels, and Machine Learning, Whistler, BC, Canada, December 10, 2010)},
howpublished = {arXiv:1010.3043},
month = oct,
year = {2010},
link = {http://arxiv.org/abs/1010.3043},
group = {techreport}
}
Tutorials
Chi, J. T. and Chi, E. C. (2014, March). Getting to the Bottom of Matrix Completion and Nonnegative Least Squares with the MM Algorithm. StatisticsViews.com.
@misc{ChiChiMMAlgorithm,
author = {Chi, Jocelyn T. and Chi, Eric C.},
title = {Getting to the Bottom of Matrix Completion and Nonnegative Least Squares with the MM Algorithm},
howpublished = {StatisticsViews.com},
month = mar,
year = {2014},
pdf = {http://jocelynchi.com/pdf/gettingtothebottom_majorization_minimization_R_tutorial.pdf},
link = {http://www.statisticsviews.com/details/feature/6035321/Getting-to-the-Bottom-of-Matrix-Completion-and-Nonnegative-Least-Squares-with-th.html},
group = {tutorials},
code = {http://jocelynchi.com/gettingtothebottom/software.html}
}
Chi, J. T. and Chi, E. C. (2014, January). Getting to the Bottom of Regression with Gradient Descent. StatisticsViews.com.
@misc{ChiChiGradientDescent,
author = {Chi, Jocelyn T. and Chi, Eric C.},
title = {Getting to the Bottom of Regression with Gradient Descent},
howpublished = {StatisticsViews.com},
month = jan,
year = {2014},
pdf = {http://jocelynchi.com/pdf/gettingtothebottom_gradient_descent_R_tutorial.pdf},
link = {http://www.statisticsviews.com/details/feature/5722691/Getting-to-the-Bottom-of-Regression-with-Gradient-Descent.html},
group = {tutorials},
code = {http://jocelynchi.com/gettingtothebottom/software.html}
}