Publications

• M. Kalra, M. Ferreira Da Costa, K. Lee, “Small-Noise Sensitivity Analysis of Locating Pulses in the Presence of Adversarial Perturbation,” submitted to IEEE Sensor Array and Multichannel (SAM) 2024 Workshop, arXiv:2403.03294.
• M. Kalra and K. Lee, “Stable estimation of pulses of unknown shape from multiple snapshots via ESPRIT,” submitted to IEEE Transactions on Signal Processing, arXiv:2308.16265.

• S. Kim and K. Lee, “Max-affine regression via first-order methods,” accepted to SIAM Journal on Mathematics of Data Science, arXiv:2308.08070.
• S. Kim, S. Bahmani, and K. Lee, “Max-Linear Regression by Scalable and Guaranteed Convex Programming,” IEEE Transactions on Information Theory, 2023.
• R.S. Srinivasa, S. Kim, K. Lee, “Sketching low-rank matrices with a shared column space by convex programming, ” IEEE Journal on Selected Areas on Information Theory, 2023.
• K. Lee and D. Stöger, “Randomly Initialized Alternating Least Squares: Fast Convergence for Matrix Sensing,” SIAM Journal on Mathematics of Data Science, 2023.
• K. Lee, R.S. Srinivasa, M. Junge, J. Romberg, “Approximately lowrank recovery from noisy and local measurements by convex program,” Information and Inference, 2023.
• S. Bahmani and K. Lee, “Low-Rank Matrix Estimation From Rank-One Projections by Unlifted Convex Optimization,” SIAM Journal on Matrix Analysis and Applications, 2021.
• M. Junge and K. Lee, “Generalized notion of sparsity and restricted isometry property. Part II: Applications,” Journal of Fourier Analysis and Applications, 2021.
• N. Tian, K. Lee, J. Romberg, N. Durofchalk, and K. Sabra, “Blind deconvolution of sources of opportunity in ocean waveguides using bilinear channel models,” The Journal of the Acoustical Society of America, 2020.
• S. Mulleti, K. Lee, and Y. Eldar, “Identifiability Conditions for Compressive Multichannel Blind Deconvolution,” IEEE Transactions on Signal Processing, 2020.
• K. Lee, S. Bahmani, Y. Eldar, and J. Romberg, “Phase retrieval of low-rank matrices by anchored regression,” Information and Inference, 2020.
• M. Junge and K. Lee, “Generalized notion of sparsity and restricted isometry property. Part I: A unified framework,” Information and Inference, 2019.
• Y. Li, K. Lee, and Y. Bresler, “Blind gain and phase calibration via sparse spectral methods,” IEEE Transactions on Information Theory, 2018.
• K. Lee, F. Krahmer, and J. Romberg, “Spectral methods for passive imaging: Non-asymptotic performance and robustness,” accepted to SIAM Journal of Imaging Science, 2018.
• K. Lee, Y. Li, K.H. Jin, and J.C. Ye, “Unified theory for recovery of sparse signals in a general transform domain,” IEEE Transactions on Information Theory 64, no. 8 (2018): 5457-5477.
• K. Lee, N. Tian, and J. Romberg, “Fast and guaranteed blind multichannel deconvolution under a bilinear system model,” IEEE Transactions on Information Theory 64, no. 7 (2018): 4792-4818.
• K. Lee, Y. Wu, and Y. Bresler, “Near optimal compressed sensing of a class of sparse low-rank matrices via sparse power factorization,” IEEE Transactions on Information Theory 64, no. 3 (2018): 1666-1698.
• Y. Li, K. Lee, and Y. Bresler, “Identifiability and stability in blind deconvolution under minimal assumptions,” IEEE Transactions on Information Theory 63, no. 7 (2017): 4619-4633.
• Y. Li, K. Lee, and Y. Bresler, “Identifiability in bilinear inverse problems with applications to subspace or sparsity-constrained blind gain and phase calibration,” IEEE Transactions on Information Theory 63, no. 2 (2017): 822-842.
• K. Lee, Y. Li, M. Junge, and Y. Bresler, “Blind recovery of sparse signals from subsampled convolution,” IEEE Transactions on Information Theory 63, no. 2 (2017): 802-821.
• J.C. Ye, J.M. Kim, K.H. Jin, and K. Lee, “Compressive sampling using annihilating filter-based low rank interpolation,” IEEE Transactions on Information Theory 63, no. 2 (2017): 777-801.
• Y. Li, K. Lee, and Y. Bresler, “Optimal sample complexity for blind gain and phase calibration,” IEEE Transactions on Signal Processing 64, no. 21 (2016): 5549-5556.
• Y. Li, K. Lee, and Y. Bresler, “Identifiability in blind deconvolution with subspace or sparsity constraints,” IEEE Transactions on Information Theory 62, no. 7 (2016): 1-10.
• K. Lee, Y. Bresler, and M. Junge, “Oblique pursuits for compressed sensing,” IEEE Transactions on Information Theory 59, no. 9 (2013): 6111-6141.
• K. Lee, Y. Bresler, and M. Junge, “Subspace methods for joint sparse recovery,” IEEE Transactions on Information Theory 58, no. 6 (2012): 3613-3641.
• K. Lee and Y. Bresler, “ADMiRA: Atomic decomposition for minimum rank approximation,” IEEE Transactions on Information Theory 56, no. 9 (2010): 4402-4416. (Correction: IEEE Transactions on Information Theory 59, no.7 (2013): 4730-4732.)
• D.S. Kim and K. Lee, “Block-coordinate Gauss-Newton optimization and constrained monotone regression for image registration in the presence of outlier objects,” IEEE Transactions on Image Processing 17, no. 5 (2008): 798-810.
• K. Lee, D.S. Kim, and T. Kim, “Regression-based prediction for blocking artifact reduction in JPEG compressed images,” IEEE Transactions on Image Processing 14, no. 1 (2005): 36-48.
• T.Y. Kim, H. Choi, K. Lee, and T. Kim, “An asymmetric watermarking system with many embedding watermarks corresponding to one detection watermark,” IEEE Signal Processing Letters 11, no. 3 (2004): 375-377.
• H. Choi, K. Lee, and T. Kim, “Transformed-key asymmetric watermarking system,” IEEE Signal Processing Letters 11 no. 2 (2004): 251-254.
• J.L. Kim, K. Lee, and T. Kim, “Adaptive reconstruction for embedded quantisation,” IEE Electronics Letters 38, no. 18 (2002): 1065-1067.

Conference Papers

• S. Kim and K. Lee, “Sequence of Linear Program for Robust Phase Retrieval,” ICASSP, 2024.
• S. Kim and K, Lee, “Fast max-affine regression via stochastic gradient descent,” 59th Annual Allerton Conference on Communication, Control, and Computing, 2023.
• M. Kalra and K. Lee, “Stability Analysis of Resolving Pulses of Unknown Shape from Compressive Fourier Measurements,” 14th International Conference on Sampling Theory and Applications (SampTA), 2023.
• M. Kalra, K. Lee, and Y. Bresler, “Identification of Pulse Streams of Unknown Shape from Time Encoding Machine Samples,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022.
• Mulleti, K. Lee, and Y.C. Eldar, “Sub-Nyquist Multichannel Blind Deconvolution,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021.
• S. Zhao, L. Potter, K. Lee, and R. Ahmad, “Convolutional Framework for Accelerated Magnetic Resonance Imaging, ” IEEE International Symposium on Biomedical Imaging (ISBI), 2020.
• R.S. Srinivasa, K. Lee, M. Junge, and J. Romberg, “Decentralized sketching of low rank matrices,” Advances in Neural Information Processing Systems (NeurIPS), 2019.
• K. Lee, R.S. Srinivasa, M. Junge, and J. Romberg, “Entropy Estimates on Tensor Products of Banach Spaces and Applications to Low-Rank Recovery,” 13th International Conference on Sampling Theory and Applications (SampTA), 2019.
• S. Bahmani and K. Lee, “”Matrix “Desketching”: Unlifted but Convex,’ Signal Processing with Adaptive Sparse Structured Representations (SPARS) workshop, 2019.
• K. Lee, F. Krahmer, and J. Romberg, “An eigen approach to stable multichannel blind deconvolution under an FIR subspace model,” Proceedings of to 12th International Conference on Sampling Theory and Applications (SampTA).
• Y. Li, K. Lee, and Y. Bresler, “Blind gain and phase calibration for low-dimensional or sparse signal sensing via power iteration,” Proceedings of the 12th International Conference on Sampling Theory and Applications (SampTA).
• Y. Li, K. Lee, and Y. Bresler, “Blind deconvolution with sparsity: optimal identifiabiliy conditions and efficient recovery,” Asilomar Conf. Signals, Systems, and Computers, 2016.
• Y. Li, K. Lee, and Y. Bresler, “Optimal sample complexity for stable matrix recovery,” in IEEE International Symposium on Information Theory (ISIT), Barcelona, Spain, Jul., 2016.
• V. B. Krishna, K. Lee, G. A. Weaver, R. K. Iyer, W. H. Sanders, “F-DETA: A framework for detecting electricity theft attacks in smart grids,” in 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2016.
• Y. Li, K. Lee, and Y. Bresler, “Identifiability of blind deconvolution with subspace or sparsity constraints,” in Signal Processing with Adaptive Sparse Structured Representations (SPARS) 2015 (best student paper award).
• K. Lee, Y. Li, M. Junge, and Y. Bresler, “Stability in blind deconvolution of sparse signals and reconstruction by alternating minimization,” in 11th International Conference on Sampling Theory and Applications (SampTA), 2015.
• Y. Li, K. Lee, and Y. Bresler, “Uniqueness in bilinear inverse problems with applications to subspace and joint sparsity models”, in 11th International Conference on Sampling Theory and Application (SampTA), 2015.
• K. Lee, Y. Bresler, and M. Junge, “Oblique pursuits for compressed sensing with random anisotropic measurements,” in IEEE International Symposium on Information Theory (ISIT), Istanbul, Turkey, Jul. 2013.
• K. Lee and Y. Bresler, “Subspace-augmented MUSIC for joint sparse recovery with any rank,” in Sensor Array and Multichannel Signal Processing Workshop (SAM), Israel, Oct. 2010.
• K. Lee and Y. Bresler, “Efficient and guaranteed rank minimization by atomic decomposition,” in IEEE International Symposium on Information Theory (ISIT), Seoul, Korea, Jun. 2009.
• K. Lee and Y. Bresler, “Computing performance guarantees for compressed sensing,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Las Vegas, NV, Apr. 2008.
• D.S. Kim and K. Lee, “Constrained monotone regression and outlier detection for searching occlusion objects,” in Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, Nov. 2007.
• D.S. Kim and K. Lee, “Block-coordinate Gauss-Newton regression method for image registration with efficient outlier detection,” in International Conference on Image Processing (ICIP), San Antonio, TX, Sep. 2007.
• D.S. Kim, K. Lee, K.E. Lee, S.S. Han, “Joint optimization of spatial registration and histogram compensation for microscopic images,” in IEEE Engineering in Medicine and Biology Society (EMBS), New York City, Aug. 2006.
• M. Boutin, K. Lee, and M. Comer, “Lossless shape representation using invariant statistics: the case of point-sets,” in Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, Oct. 2006.
• D.S. Kim, S.Y. Lee, and K. Lee, “Joint optimization of image registration and comparametric exposure compensation based on the Lucas-Kanade algorithm,” in International Conference on Pattern Recognition, Hong Kong, Aug. 2006.
• D.S. Kim, S.Y. Lee, and K. Lee, “Empirical conditional mean: nonparametric estimator for comparametric Exposure Compensation,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Toulouse, France, May 2006.
• K. Lee, D.S. Kim, T. Kim, and K.A. Moon, “EM estimation of scale factor for quantization-based audio watermarking,” in International Workshop on Digital-forensics and Watermarking, Seoul, Korea, Oct. 2003 (best paper award).
• T.Y. Kim, T. Kim, and K. Lee, “Generation of embedding watermark signals from reference watermark of the detector,” in IEEE International Symposium on Circuits and Systems (ISCAS), Bangkok, Thailand, May 2003.
• K. Lee, D.S. Kim, and K.A. Moon, “Amplitude-modification resilient watermarking based on A-law companding,” in International Conference on Image Processing (ICIP), Barcelona, Spain, Sep. 2003.
• D.S. Kim and K. Lee, “Training sequence size in clustering algorithms and averaging single-particle images,” in International Conference on Image Processing (ICIP), Barcelona, Spain, Sep. 2003
• K. Lee, D.S. Kim, and T. Kim, “A new postprocessing algorithm based on regression functions,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Orlando, FL, May 2002.

Technical Report

• K. Lee, E. Yarkony, and Y. Bresler, “Subsampled multichannel blind deconvolution using sparse power factorization,” CSL Technical Report UILU-ENG-13-2207, University of Illinois, Sep. 2013.

Patents & Applications

• Y. Hwang, K. Lee, K.A. Moon, M.J. Kim, “Method of designing watermark in consideration of Wiener attack and whitening filtered detection,” US patent 7076081.
• J.C. Ye, J.M. Kim, O.K. Lee, Y. Bresler, and K. Lee, “Method and apparatus for compressed sensing with joint sparsity,” US patent application, 20120259590.
• K. Lee, D.S. Kim, K.A. Moon, Y.H. Suh, “Amplitude-scaling resilient audio watermarking method and apparatus based on quantization,” US patent application 20050043830.
• K. Lee, D.S. Kim, K.A. Moon, “Apparatus and method for digital watermarking using nonlinear quantization,” US patent application 20050137876.