Eric Chi

Heng, Q., Zhou, H., & Chi, E. C. (2023, February 24). Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, Vol. 2. https://doi.org/10.1080/10618600.2023.2170089

Heng, Q., Chi, E. C., & Liu, Y. (2023, May 20). Robust Low-Rank Tensor Decomposition with the L-2 Criterion. TECHNOMETRICS. https://doi.org/10.1080/00401706.2023.2200541

Liu, X., Chi, E. C., & Lange, K. (2022, October 6). A Sharper Computational Tool for L2E Regression. TECHNOMETRICS, Vol. 10. https://doi.org/10.1080/00401706.2022.2118172

Chi, J. T., & Chi, E. C. (2022). A User-Friendly Computational Framework for Robust Structured Regression with the L2 Criterion. Journal of Computational and Graphical Statistics. https://doi.org/10.1080/10618600.2022.2035232

Liu, X., & Chi, E. C. (2022). Revisiting convexity-preserving signal recovery with the linearly involved GMC penalty. PATTERN RECOGNITION LETTERS, 156, 60–66. https://doi.org/10.1016/j.patrec.2022.02.004

Liu, X., Vardhan, M., Wen, Q., Das, A., Randles, A., & Chi, E. C. (2021). An Interpretable Machine Learning Model to Classify Coronary Bifurcation Lesions. 2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC), pp. 4432–4435. https://doi.org/10.1109/embc46164.2021.9631082

Yi, H., Huang, L., Mishne, G., & Chi, E. C. (2021). COBRAC: a fast implementation of convex biclustering with compression. BIOINFORMATICS, 37(20), 3667–3669. https://doi.org/10.1093/bioinformatics/btab248

Chi, E. C. (2021). Discovering Geometry in Data Arrays. Computing in Science & Engineering, 23(6), 42–51. https://doi.org/10.1109/MCSE.2021.3120039

Zhang, M., Mishne, G., & Chi, E. C. (2021, November 5). Multi-scale affinities with missing data: Estimation and applications. STATISTICAL ANALYSIS AND DATA MINING. https://doi.org/10.1002/sam.11561

Vardhan, M., Gounley, J., Chen, S. J., Chi, E. C., Kahn, A. M., Leopold, J. A., & Randles, A. (2021). Non-invasive characterization of complex coronary lesions. SCIENTIFIC REPORTS, 11(1). https://doi.org/10.1038/s41598-021-86360-6

Zhou, W., Yi, H., Mishne, G., & Chi, E. (2021). SCALABLE ALGORITHMS FOR CONVEX CLUSTERING. 2021 IEEE DATA SCIENCE AND LEARNING WORKSHOP (DSLW). https://doi.org/10.1109/DSLW51110.2021.9523411

Feng, Y., Xiao, L., & Chi, E. C. (2021). Sparse Single Index Models for Multivariate Responses. Journal of Computational and Graphical Statistics, 30(1), 115–124. https://doi.org/10.1080/10618600.2020.1779080

Brantley, H. L., Guinness, J., & Chi, E. C. (2020). BASELINE DRIFT ESTIMATION FOR AIR QUALITY DATA USING QUANTILE TREND FILTERING. ANNALS OF APPLIED STATISTICS, 14(2), 585–604. https://doi.org/10.1214/19-AOAS1318

Rhyne, J., Jeng, X. J., Chi, E. C., & Tzeng, J.-Y. (2020). FastLORS: Joint modelling for expression quantitative trait loci mapping in R. STAT, 9(1). https://doi.org/10.1002/sta4.265

Stanley, J. S., III, Chi, E. C., & Mishne, G. (2020). Multiway Graph Signal Processing on Tensors: Integrative Analysis of Irregular Geometries. IEEE SIGNAL PROCESSING MAGAZINE, 37(6), 160–173. https://doi.org/10.1109/MSP.2020.3013555

Chi, E. C., Gaines, B. J., Sun, W. W., Zhou, H., & Yang, J. (2020). Provable Convex Co-clustering of Tensors. Journal of Machine Learning Research, 21(214), 1–58. Retrieved from http://jmlr.org/papers/v21/18-155.html

Mishne, G., Chi, E., & Coifman, R. (2019). Co-manifold learning with missing data. In K. Chaudhuri & R. Salakhutdinov (Eds.), International Conference on Machine Learning (Vol. 97, pp. 4605–4614). Retrieved from http://proceedings.mlr.press/v97/mishne19a.html

Chi, E. C., Hu, L., Saibaba, A. K., & 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. https://doi.org/10.1080/10618600.2018.1482763

Chi, E. C., & Li, T. (2019). [Review of Matrix completion from a computational statistics perspective]. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS, 11(5). https://doi.org/10.1002/wics.1469

Chi, E., & Steinerberger, S. (2019). Recovering Trees with Convex Clustering. SIAM Journal on Mathematics of Data Science, 1(3), 383–407. https://doi.org/10.1137/18m121099x

Lusch, B., Chi, E. C., & Kutz, J. N. (2019). Shape Constrained Tensor Decompositions. 2019 IEEE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND ADVANCED ANALYTICS (DSAA 2019), pp. 287–297. https://doi.org/10.1109/DSAA.2019.00044

Min, E. J., Chi, E. C., & Zhou, H. (2019). Tensor canonical correlation analysis. Stat, 8(1). https://doi.org/10.1002/sta4.253

Xu, J., Chi, E. C., Yang, M., & Lange, K. (2018). A majorization-minimization algorithm for split feasibility problems. COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 71(3), 795–828. https://doi.org/10.1007/s10589-018-0025-z

Chi, E. C., Allen, G. I., & Baraniuk, R. G. (2017). Convex Biclustering. BIOMETRICS, 73(1), 10–19. https://doi.org/10.1111/biom.12540

Xu, J., Chi, E., & Lange, K. (2017). Generalized Linear Model Regression under Distance-to-set Penalties. In I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, & R. Garnett (Eds.), Neural Information Processing Systems (pp. 1385–1395). Retrieved from https://papers.nips.cc/paper/6737-generalized-linear-model-regression-under-distance-to-set-penalties

Long, J. P., Chi, E. C., & Baraniuk, R. G. (2016). ESTIMATING A COMMON PERIOD FOR A SET OF IRREGULARLY SAMPLED FUNCTIONS WITH APPLICATIONS TO PERIODIC VARIABLE STAR DATA. ANNALS OF APPLIED STATISTICS, 10(1), 165–197. https://doi.org/10.1214/15-aoas885

Chi, J. T., Chi, E. C., & Baraniuk, R. G. (2016). k-POD: A Method for k-Means Clustering of Missing Data. AMERICAN STATISTICIAN, 70(1), 91–99. https://doi.org/10.1080/00031305.2015.1086685

Chen, G. K., Chi, E. C., Ranola, J. M. O., & Lange, K. (2015). Convex Clustering: An Attractive Alternative to Hierarchical Clustering. PLoS Computational Biology, 11(5), e1004228. https://doi.org/10.1371/journal.pcbi.1004228

Chi, E. C., & Lange, K. (2015). Splitting Methods for Convex Clustering. Journal of Computational and Graphical Statistics, 24(4), 994–1013. https://doi.org/10.1080/10618600.2014.948181

Lange, K., Chi, E. C., & Zhou, H. (2014). A Brief Survey of Modern Optimization for Statisticians. INTERNATIONAL STATISTICAL REVIEW, 82(1), 46–70. https://doi.org/10.1111/insr.12022

Chi, E. C., & Lange, K. (2014). A Look at the Generalized Heron Problem through the Lens of Majorization-Minimization. The American Mathematical Monthly, 121(2), pp. 95–108. https://doi.org/10.4169/amer.math.monthly.121.02.095

Chi, E. C., Zhou, H., & Lange, K. (2014). Distance majorization and its applications. MATHEMATICAL PROGRAMMING, 146(1-2), 409–436. https://doi.org/10.1007/s10107-013-0697-1

Lange, K., Chi, E. C., & Zhou, H. (2014). Rejoinder. INTERNATIONAL STATISTICAL REVIEW, 82(1), 81–89. https://doi.org/10.1111/insr.12030

Chi, E. C., & 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. https://doi.org/10.1080/10618600.2012.737296

Chi, E. C., & Lange, K. (2014). Stable estimation of a covariance matrix guided by nuclear norm penalties. Computational Statistics & Data Analysis, 80(0), 117–128. https://doi.org/10.1016/j.csda.2014.06.018

Chi, E. C., Zhou, H., Chen, G. K., Del Vecchyo, D. O., & Lange, K. (2013). Genotype imputation via matrix completion. GENOME RESEARCH, 23(3), 509–518. https://doi.org/10.1101/gr.145821.112

Chi, E. C., Allen, G. I., Zhou, H., Kohannim, O., Lange, K., & Thompson, P. M. (2013). Imaging genetics via sparse canonical correlation analysis. Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on, 740–743. https://doi.org/10.1109/ISBI.2013.6556581

Chi, E., & Kolda, T. (2012). On Tensors, Sparsity, and Nonnegative Factorizations. SIAM Journal of Matrix Analysis and Applications, 33(4), 1272–1299. https://doi.org/10.1137/110859063

Chi, E. C., Mende, S. B., Fok, M.-C., & Reeves, G. D. (2006). Proton auroral intensifications and injections at synchronous altitude. Geophysical Research Letters, 33(6). https://doi.org/10.1029/2005GL024656

Gupta, R., Chi, E., & Walrand, J. (2005). Different Algorithms for Normal and Protection Paths. Journal of Network and Systems Management, 13(1), 13–33. https://doi.org/10.1007/S10922-005-1845-6

Chi, E., Fu, M., & Walrand, J. (2004). Proactive resource provisioning. Computer Communications, 27(12), 1174–1182. https://doi.org/10.1016/j.comcom.2004.02.019

Chi, E., Fu, M., & Walrand, J. (2004). Proactive resource provisioning. Computer Communications, 27(12), 1174–1182. https://doi.org/10.1016/S0140-3664(04)00111-2