Book Chapters

  1. D. Donoho and X. Huo (2002). Beamlets and multiscale image analysis. In Multiscale and Multiresolution Methods. Eds. T. J. Barth, T. Chan, and R. Haimes, Springer Lecture Notes in Computational Science and Engineering, 20: 149-196.
  2. X. Huo (2005). Beamlets and multiscale modeling. Entry for the 2nd Edition of Encyclopedia of Statistical Sciences, Eds. C. B. Read, N. Balakrishnan, and B. Vidakovic, Wiley & Sons, NJ.
  3. X. Huo and X. S. Ni (2007). Some recent results in model selection. In Quantitative Medical Data Analysis Using Mathematical Tools and Statistical Techniques, Eds. D. Hong and Y. Shyr. World Scientific Publication, Singapore. Page 25-42.
  4. X. Huo, X. S. Ni, and A. K. Smith (2007). A survey of manifold-based learning methods. In Recent Advances in Data Mining of Enterprise Data, T. W. Liao and E. Triantaphyllou (Eds.) World Scientific, Singapore, pp 691-745, January.

Journal Papers

  1. D. Donoho and X. Huo (2001). Uncertainty principles and ideal atomic decomposition. IEEE Transactions on Information Theory, 47 (7): 2845-2862, November.
  2. D. Chen, J. C. Lu, X. Huo, and M. Yin (2001). Optimum percentile estimating equations for nonlinear random coefficient models. Journal of Statistical Planning and Inference, 97 (2): 275-292, September.
  3. X. Huo (2002). Multiscale Approximation MEthods (MAME) to locate embedded consecutive subsequences–its applications in statistical data mining and spatial statistics. Computers & Industrial Engineering, 43 (4): 703-720, September.
  4. X. Huo (2004). A statistical analysis of Fukunaga Koontz transform. IEEE Signal Processing Letters, 11 (2): 123-126, February.
  5. X. Huo and Jihong Chen (2004). Building a cascade detector and its applications in automatic target recognition. Applied Optics: Information Processing (IP), 43 (2): 293-303, January.
  6. X. Huo and J. Lu (2004). A network flow approach in finding maximum likelihood estimate of high concentration regions. Computational Statistics and Data Analysis, 46 (1): 33-56, May.
  7. D. L. Donoho and X. Huo (2004). BeamLab and reproducible research. International Journal of Wavelets, Multiresolution and Information Processing (IJWMIP), 2 (4): 391-414, December.
  8. X. Huo (2005). Minimax correlation between a line segment and a beamlet. Statistics & Probability Letters, 72 (1): 71-81, April.
  9. X. Huo (2005). Exact lower bound for proportion of maximally embedded beamlet. Applied Mathematics Letters, 18 (5): 529-534, May.
  10. E. Arias-Castro, D. L. Donoho and X. Huo (2005). Near-optimal detection of geometric objects by fast multiscale methods. IEEE Trans. Information Theory, 51 (7): 2402-2425, July.
  11. E. Arias-Castro, D. L. Donoho, X. Huo, and C. Tovey (2005). Connect-the-dots: how many random points can a regular curve pass through? Advances in Applied Probability, 37 (3), 571-603, September.
  12. X. Huo and Jihong Chen (2005). JBEAM: multiscale curve coding via beamlets. IEEE Trans. Image Processing, 14 (11), 1665-1677, November.
  13. E. Arias-Castro, D. L. Donoho and X. Huo (2006). Adaptive multiscale detection of filamentary structures embedded in a background of Uniform random points. Annals of Statistics, 34 (1), 326-349, February.
  14. M. K. Jeong, J.C. Lu, X. Huo, B. Vidakovic, and D. Chen (2006). Wavelet-based data reduction techniques for process fault detection. Technometrics, 48 (1), 26-40, February. (Invited presentation in Technometrics session, QSR cluster, in 2005 Informs Annual Meeting at San Francisco, CA.)
  15. Jihong Chen and X. Huo (2006). Distribution of the length of the longest significance run on a Bernoulli net, and its applications. Journal of the American Statistical Association, 101 (473), 321-331, March.
  16. X. Huo, S. B. Kim, K. L. Tsui, and S. Wang (2006). FBP: A frontier-based tree-pruning algorithm. INFORMS Journal on Computing, 18 (4): 494-505, Fall.
  17. Jie Chen and X. Huo (2006). Theoretical results on sparse representations of Multiple Measurement Vectors. IEEE Trans. Signal Processing, 54 (12): 4634-4643, December.
  18. X. S. Ni and X. Huo (2007). Statistical interpretation of the importance of phase information in signal and image reconstruction. Statistics and Probability Letters, 77 (4): 447-454, February.
  19. X. Huo and X. S. Ni (2007). When do stepwise algorithms meet subset selection criteria? Annals of Statistics, 35 (2): 870-887, April.
  20. J. Chen, S. Deng, and X. Huo (2008). Electricity price curve modeling and forecasting by manifold learning. IEEE Trans. on Power Systems, 23 (3): 877-888, August.
  21. X. S. Ni and X. Huo (2009). Another look at Huber’s estimator: a new minimax estimator in regression with stochastically bounded noise. Journal of Statistical Planning & Inference, 139 (2): 503-515, February.
  22. X. Huo and A. K. Smith (2009). Matrix perturbation analysis of local tangent space alignment. Linear Algebra & Its Applications, 430: 732-746, January.
  23. X. Huo and X. S. Ni (2009). Detectability of convex-shaped objects in digital images, its fundamental limit and multiscale analysis. Statistica Sinica, 19 (4): 1439-1462, October.
  24. J. Chen and X. Huo (2009). A Hessian regularized nonlinear time series model. Journal of Computational and Graphical Statistics, 18 (3): 694-716, September.
  25. X. Huo and J. Chen (2010). Complexity of penalized likelihood estimation. Journal of Statistical Computation and Simulations. To appear.
  26. S. B. Kim , X. Huo , and K.-L. Tsui (2010). A finite-sample simulation study of cross validation in tree-based models. Accepted by Information Technology and Management. To appear.

Conference Papers

  1. D. Donoho and X. Huo (1997). Large-sample modulation classification using Hellinger representation. Proc. Signal Processing Advances on Wireless Communication (SPAWC), Paris, France.
  2. X. Huo and S. Liu (1998). Stochastic behavior of inter-drop time in an M-buffer video decoding scenario. International Conference on Image Processing (ICIP), Chicago, IL. (ICIP is a top international conference on image processing.)
  3. X. Huo and D. Donoho (1998). A simple and robust modulation classification method via counting. International Conference on Acoustic Speech and Signal Processing (ICASSP), Seattle, WA. (ICASSP is a top international conference on signal processing.)
  4. X. Huo and A. Stoschek (1999). Experiments with combined image transforms and its implications in biomedical image analysis. First USF International Workshop on Digital and Computational Video (DCV), Tampa, FL.
  5. D. Donoho and X. Huo (1999). Combined image representation using edgelets and wavelets. Published in Wavelet Applications in Signal and Image Processing VII. Presented in SPIE, Denver, CO.
  6. D. Donoho and X. Huo (2000). Beamlet pyramids: a new form of multiresolution analysis, suited for extracting lines, curves and objects from very noisy image data. Published in Wavelet applications in signal and image processing VIII. Presented in SPIE, San Diego, CA.
  7. D. Donoho and X. Huo (2001). Applications of beamlets to detection and extraction of lines, curves and objects in very noisy images. Nonlinear Signal and Image Processing (NSIP), Baltimore, MD, June.
  8. X. Huo and D. Donoho (2002). Recovering filamentary objects in severely degraded binary images using beamlet-decorated partitioning. International Conference on Acoustic Speech and Signal Processing, (ICASSP), Orlando, FL, May.
  9. X. Huo and Jihong Chen (2002). Local linear projection (LLP). First IEEE Workshop on Genomic Signal Processing and Statistics (GENSIPS), Raleigh, NC, October.
  10. Jihong Chen and X. Huo (2002). Beamlet coder: a tree-based, hierarchical contour representation and coding method. ICASSP, Orlando, FL, May.
  11. X. Huo, Jihong Chen, and D.L. Donoho (2003). Multiscale detection of filamentary features in image data. SPIE Wavelet-X, San Diego, CA, August.
  12. X. Huo, M. Elad, A. G. Flesia, B. Muise, R. Stanfill, J. Friedman, B. Popescu, Jihong Chen, A. Mahalanobis, and D. L. Donoho (2003). Optimal reduced-rank quadratic classifiers using the Fukunaga-Koontz transform, with applications to automated target recognition. SPIE’s 7th Annual International Symposium on Aerospace/Defense Sensing, Simulation, and Controls (AeroSense), Orlando, FL, April.
  13. X. Huo (2003). A geodesic distance and local smoothing based clustering algorithm to utilize embedded geometric structures in high dimensional noisy data. SIAM International Conference on Data Mining, Workshop on Clustering High Dimensional Data and its Applications, San Francisco, CA, May.
  14. X. Huo, Jihong Chen and D. L. Donoho (2003). Multiscale significance run: realizing the `most powerful’ detection in noisy images. Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November.
  15. X. Huo and Jihong Chen (2004). Detecting the presence of an inhomogeneous region in a homogeneous background: taking advantages of the underlying geometry via manifolds. ICASSP, Montreal, Quebec, Canada, May.
  16. X. Huo, Jihong Chen, and D. L. Donoho (2004). Coding lines and curves via digital beamlets. Data Compression Conference (DCC), Snowbird, UT, March. (DCC is a top international conference on data compression.)
  17. Jie Chen and Xiaoming Huo (2005). Sparse representations for Multiple Measurement Vectors (MMV) in an over-complete dictionary. ICASSP, Philadelphia, PA, March.
  18. X. S. Ni and X. Huo (2005). Enhanced leaps-and-bounds methods in subset selections with additional optimality tests. (One of four finalists in the INFORMS QSR Best Student Paper Competition; activities.htm.)
  19. X. Huo (2006). Some recent results on the performance and implementation of manifold learning algorithms. Proceedings of AI/DM workshop prior to the INFORMS Annual Meeting, Pittsburgh, PA, November.
  20. A. K. Smith, X. Huo, and H. Zha (2008). Convergence and rate of convergence of a manifold-based dimension reduction algorithm. NIPS (a prestigious conference in computer science). Vancouver, Canada, December.