- James B. Duke Professor of Mathematics and Electrical and Computer Engineering
- Professor in the Department of Mathematics
- Professor in the Department of Electrical and Computer Engineering (Joint)
Research Areas and Keywords
Geometry: Differential & Algebraic
Signals, Images & Data
Zou, J., et al. “Theoretical and experimental analysis of a randomized algorithm for Sparse Fourier transform analysis.” Journal of Computational Physics, vol. 211, no. 2, Jan. 2006, pp. 572–95. Scopus, doi:10.1016/j.jcp.2005.06.005. Full Text
Roussos, E., et al. “Variational Bayesian learning for wavelet independent component analysis.” Aip Conference Proceedings, vol. 803, Nov. 2005, pp. 274–81. Scopus, doi:10.1063/1.2149805. Full Text
Daubechies, I., and G. Teschke. “Variational image restoration by means of wavelets: Simultaneous decomposition, deblurring, and denoising.” Applied and Computational Harmonic Analysis, vol. 19, no. 1, July 2005, pp. 1–16. Scopus, doi:10.1016/j.acha.2004.12.004. Full Text
Pierpaoli, E., et al. “Reconstructing Sunyaev-Zel'dovich clusters in future cosmic microwave background experiments.” Monthly Notices of the Royal Astronomical Society, vol. 359, no. 1, May 2005, pp. 261–71. Scopus, doi:10.1111/j.1365-2966.2005.08896.x. Full Text
Daubechies, I., and E. H. Lieb. One-electron relativistic molecules with coulomb interaction. Jan. 2005, pp. 471–84. Scopus, doi:10.1007/3-540-27056-6_33. Full Text
Daubechies, I., et al. “A detailed study of the attachment strategies of new autonomous systems in the as connectivity graph.” Internet Mathematics, vol. 2, no. 2, Jan. 2005, pp. 185–246. Scopus, doi:10.1080/15427951.2005.10129103. Full Text
Rudin, C., et al. “Boosting based on a smooth margin.” Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), vol. 3120, Dec. 2004, pp. 502–17.
Rudin, C., et al. “The dynamics of AdaBoost: Cyclic behavior and convergence of margins.” Journal of Machine Learning Research, vol. 5, Dec. 2004, pp. 1557–95.
Daubechies, I., et al. “An iterative thresholding algorithm for linear inverse problems with a sparsity constraint.” Communications on Pure and Applied Mathematics, vol. 57, no. 11, Nov. 2004, pp. 1413–57. Scopus, doi:10.1002/cpa.20042. Full Text