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Michael Zibulevsky
Medium homepage: https://medium.com/@michaelzibulevsky
Михаил Цыбулевский,Технион
Цыбулевский Михаил Леонидович
מיכאל ציבולבסקי
Principal Research Fellow
Department of Computer Science
Technion - Israel Institute of Technology
Email: mzib@cs.technion.ac.il, mzibul@gmail.com
Tel: 054-784-7738
Research Interests
Numerical optimization, deep learning, sparse signal representations, independent component analysis, inverse problems in medical imaging
Teaching
Discussion group
YouTube video
NEW:
Radiation design in computed tomography via convex optimization https://youtu.be/PuW4bcbmYqw
Neural Networks
Нейронные сети для умных чайников - 2. Универсальное приближение функций; Сверточные и U-сети NEW
An easy way to compute Jacobian and gradient with forward and back propagation in a graph
Elad Hoffer, Deep Learning course, Technion, 2016 (in Hebrew): Lecture 2, Lecture 3, Lecture 4, Lecture 5
End-to-End Deep Learning: Applications in Speech, by Yedid Hoshen
Lecture 2-3: Gradient and Hessian of Multivariate Function (enhanced)
Easy way to compute Jacobian and gradient with forward and back propagation in graph
Lecture 6 (enhanced).Local and global minimum. Sufficient and necessary optimality conditions
Bisection method for finding root and minimum of 1D function
Newton method for multidimensional minimization. Part 1 Part 2
Newton and Gauss-Newton methods for nonlinear system of equations and least squares problem
Conjugate gradient method
Quasi-Newton Optimization Methods (BFGS, L-BFGS, etc.)
Penalty function and Augmented Lagrangian methods 2013 (Introduction)
Penalty Multiplier Method (Augmented Lagrangian) 2: Dual Interpretation
In-class recordings:
Constrained optimization, Class 14 05 2019: Lagrange multipliers, KKT conditions, Penalty function method
Part 1, Part 2, Part 3Augmented Lagrangian and ADMM, Class 21 05 2019: Part 1, Part 2
Zoom lecture: Differential of a multivariate function 22.04.2020
Zoom Lecture 4: 1D optimization methods and line search, 22.04.2020
Zoom Lecture 5b: Steepest Descent, Newton, Gauss-Newton. 06.05.2020
Zoom Lecture 6: Conjugate Gradient Method 13.05.2020
Zoom Lecture 8: Constrained optimization, KKT, penalty method 27.05.2020
Zoom Lecture 11, Gradient of neural network in matrix form 17.06.2020
Optimization course, reception hour 1 towards the exam, 23.07.2020
updated link: https://youtu.be/npc1_pXRYVAOptimization course, reception hour 2 towards the exam, 26.07.2020
Image / Signal Processing
School Math
Graph of Quadratic Function (in Hebrew) גרפ של פונקציה ריבועית
My short video lessons in secondary school mathematics
Society
Others
Presentations (slides)
Blind source separation by sparse decomposition + Relative Newton + Method of multipliers, Jerusalem 2004
Blind source separation, deconvolution and localization using sparse representations, 2004
SESOP: Sequential Subspace Optimization Method for large-scale optimization problems (including SESOP-TN), 2012
Matlab Code
PCD-CG: Parallel coordinate descent merged with conjugate gradients
SESOP_PACK - large-scale unconstrained optimization tool, version 10.05.2010 Includes L1-L2 optimization via PCD-SESOP (parallel coordinate descent), SSF-SESOP, FISTA, etc
Newton method with "frozen" Hessian for unconstrained optimization
Modified Cholesky Factorization (modified Brian Borchers' code)
Image Total Variation, its gradient and Hessian-vector products (simple and fast code)
Sparse ICA code (by A&M Bronstein): Blind Source Separation based on Sparse Representations
Extraction of a single source from multichannel data using template and sparse decomposition
Selected Publications
See the latest publications at my Google Scholar page:
Book Chapters:
M. Zibulevsky, B. A. Pearlmutter, P. Bofill, and P. Kisilev, "Blind Source Separation by Sparse Decomposition", chapter in the book: S. J. Roberts, and R.M. Everson eds., Independent Component Analysis: Principles and Practice, Cambridge, 2001. gzipped ps file , pdf file
M. Zibulevsky,"Relative Newton and Smoothing Multiplier Optimization Methods for Blind Source Separation", chapter in the book: S. Makino, T.W. Lee and H. Sawada eds., Blind Speech Separation, Springer Series: Signals and Communication Technology XV, 2007 pdf file
R. Gribonval and M. Zibulevsky. Sparse Component Analysis, in Pierre Comon and Christian Jutten (Editors), Handbook of Blind Source Separation: Independent Component Analysis and Applications, ELSEVIER 2010, pp.367-420
Papers and Reports:
Michael Zibulevsky (2010) How to inhibit destructive positive feedback in time of economic crisis
M. Zibulevsky and M. Elad, L1-L2 Optimization in Signal and Image Processing, IEEE Signal Processing Magazine, Vol. 27 No. 3, Pages 78-88, May 2010.
J. Shtok, M. Elad, and M. Zibulevsky, Spatially-Adaptive Reconstruction in Computed Tomography Based on Statistical Learning, Submitted to IEEE Transactions on Image Processing
Yehuda Pfeffer and Michael Zibulevsky (2010) Sampling and Noise in Compressive Sensing
Yehuda Pfeffer and Michael Zibulevsky (2010) A Micro-Mirror Array based System for Compressive Sensing of Hyperspectral Data
Master thesis of Yehuda Pfeffer "Compressive Sensing for Hyperspectral Imaging", Technion, 2010
thesis_yehuda_pfeffer
Ron Rubinstein, Michael Zibulevsky, Michael Elad, Double Sparsity: Learning Sparse Dictionaries for Sparse Signal Approximation, IEEE Transactions on Signal Processing, Vol. 58, No. 3, Pages 1553-1564, March 2010
Eliyahu Osherovich, Michael Zibulevsky, and Irad Yavneh (2009) IMAGE RECONSTRUCTION FROM NOISY FOURIER MAGNITUDE WITH PARTIAL PHASE INFORMATION
Michael Zibulevsky (2009) How to prevent economic crisis in time of disaster: consumer insurance bonds
Michael Zibulevsky (2008), On convex formulation of 1D scaling problem
Michael Zibulevsky (2008), SESOP-TN: Combining Sequential Subspace Optimization with Truncated Newton method
Alexander M. Bronstein, Michael M. Bronstein and Michael Zibulevsky, "On Separation of Semitransparent Dynamic Images from Static Background",
L. Dascal, M. Zibulevsky and R. Kimmel, "Signal denoising by constraining the residual to be statistically noise-similar", Technical Report, 2008 pdf file
A.M. Bruckstein, M. Elad, and M. Zibulevsky, On the Uniqueness of Nonnegative Sparse Solutions to Underdetermined Systems of Equations, IEEE Transactions on Information Theory, Vol. 54, No. 11, Pages 4813-4820, November 2008
Sarit Shwartz, Yoav Y. Schechner and Michael Zibulevsky (2008), Blind separation of convolutive image mixtures, To be published in Neurocomputing, Special issue on Advances in Blind Signal Processing.
M. Elad, B. Matalon, and M. Zibulevsky, "Coordinate and Subspace Optimization Methods for Linear Least Squares with Non-Quadratic Regularization", Applied and Computational Harmonic Analysis, Vol. 23, pp. 346-367, November 2007. pdf file
D. Model and M. Zibulevsky (October 2006), Learning Subject-Specic Spatial and Temporal Filters for Single-Trial EEG Classi/cation, NeuroImage, Vol 32, Issue 4, pp 1631-1641 pdf file
Model D. and Zibulevsky M. (2006), Signal Reconstruction in Sensor Arrays using Sparse Representations, Signal Processing, Vol 86, Issue 3, pp 624-638 pdf file
Shwartz S., Zibulevsky M., and Schechner Y.Y. (2005), Fast kernel entropy estimation and optimization, Signal Processing, Vol 85, pp. 1045-1058 pdf file
Narkiss, G. and Zibulevsky, M. (2005). "Sequential Subspace Optimization Method for Large-Scale Unconstrained Problems", Tech. Report CCIT No 559, EE Dept., Technion. pdf file
Narkiss, G. and Zibulevsky, M. (2005). "Support Vector Machine via Sequential Subspace Optimization", Tech. Report CCIT No 557, EE Dept., Technion. pdf file
Zibulevsky, M. (2005). "Blind Source Separation using Relative Newton Method combined with Smoothing Method of Multipliers", Tech. Report CCIT No 556, EE Dept, Technion. pdf file
A.M. Bronstein, M.M. Bronstein, M. Zibulevsky and Y.Y.Zeevi, "Sparse ICA for blind separation of transmitted and reflected images", Intl. Journal of Imaging Science and Technology (IJIST), Vol. 15/1, pp. 84-91, 2005.
A.M. Bronstein, M.M. Bronstein, M. Zibulevsky and Y.Y.Zeevi, "Blind Deconvolution of Images using Optimal Sparse Representations", IEEE Trans. on Image Processing, 14(6):726-736, June 2005. pdf file
Alexey Polonsky, Michael Zibulevsky: MEG/EEG Source Localization Using Spatio-temporal Sparse Representations. ICA 2004: 1001-1008 pdf file
A. Bronstein, M. Bronstein and M. Zibulevsky (2003), "Relative optimization for blind deconvolution", IEEE Trans. on Signal Processing, to appear. pdf file
A. Bronstein, M. Bronstein and M. Zibulevsky (2003), "Blind source separation using block-coordinate relative Newton method" pdf file
P. Kisilev, M. Zibulevsky, Y.Y. Zeevi (2003). "Multiscale framework for blind source separation", JMLR, in press. pdf file
Zibulevsky, M. "Blind Source Separation with Relative Newton Method", Proceedings ICA2003, pp. 897-902
Zibulevsky, M. and Pearlmutter, B.A. (2000). "Second order blind source separation by recursive splitting of signal subspaces", Proceedings ICA2000. gzipped ps file
Bronstein M., Bronstein A. and Zibulevsky M. (2002). ``Iterative reconstruction in diffraction tomography using non-uniform FFT'' pdf file
Bronstein A., Bronstein M., Zibulevsky M. and Zeevi Y.Y. (2002). ``Optimal nonlinear estimation of photon coordinates in PET'' pdf file
M. Zibulevsky (2003). "Smoothing Method of Multipliers for Sum-Max Problems" gzipped ps file
Bofill P., Zibulevsky, M. (2001). Underdetermined Blind Source Separation using Sparse Representations, Signal Processing, Vol.81, No 11, pp.2353-2362. pdf file
Zibulevsky, M. and Pearlmutter, B.A. (1999). "Blind Source Separation by Sparse Decomposition ", Neural Computations 13(4), 2001 gzipped ps file , zipped ps file , OLD html verson, Demo
M. Zibulevsky, Y.Y. Zeevi (2002). "Extraction of a single source from multichannel data using sparse decomposition", Neurocomputing 49, pp 163-173. gzipped ps file
M. Zibulevsky, P. Kisilev, Y.Y. Zeevi, B.A. Pearlmutter (2000). "Blind source separation via multinode sparse representation", NIPS-2001, gzipped ps file
Levkovitz R., Falikman D., Zibulevsky M., Ben-Tal A., Nemirovski A. (2001) ``The design and implementation of COSEM, an iterative algorithm for fully 3D listmode data'', IEEE Trans. Med. Imaging, v. 20, #7, pp. 633-642 pdf file
Zibulevsky, M. and Pearlmutter, B.A. (2000). "Recovering shape and distribution of delays of repetitive responses in strong noise" Technical Report CS00-1, Computer Science Department, University of New Mexico. gzipped ps file
Akaysha C. Tang, Barak A. Pearlmutter, and Michael Zibulevsky. Blind source separation of neuromagnetic responses. Computational Neuroscience 1999, proceedings published in Neurocomputing. In press.
Mosheyev, L. and Zibulevsky, M. (2000). "Penalty/Barrier Multiplier Algorithm for Semidefinite Programming", Optimization Methods and Software, vol.13, No 4, pp. 235-261. pdf file , gzipped dvi file
Zibulevsky, M. (1998). "Pattern Recognition via Support Vector Machine with Computationally Efficient Nonlinear Transform ". gzipped ps
Zibulevsky, M. (1998). "ML Reconstruction of Dynamic Pet Images from Projections and Clist ", Technical Report CS98-3, Computer Science Department, University of New Mexico. gzip ps
Ben-Tal, A. and Zibulevsky, M. (1997). ``Penalty/Barrier Multiplier Methods for Convex Programming Problems",SIAM Journal on Optimization v. 7 # 2, pp. 347-366, gzip ps
Zibulevsky M. (1996) Penalty/Barrier Multiplier Methods for Large-Scale Nonlinear and Semidefinite Programming. Ph.D. Thesis. gzip ps , gzip dvi
Kochvara, M., Zibulevsky, M. and Zowe, J. (1996). "Mechanical Design Problems with Unilateral Contact", MAN - Mathematical Modeling and Numerical Analysis, v.32, no 3, pp. 255-282
Akaysha C. Tang, Barak A. Pearlmutter, Michael Zibulevsky, Tim A. Hely, and Michael Weisend. An MEG study of response latency and variability in the human visual system during a visual-motor integration task. In Advances in Neural Information Processing Systems*99. Morgan Kaufmann, 2000, to appear.
Greig, D., Siegelman, H. and Zibulevsky, M., (1996). "A New Class of Neural Network Activation Functions That Don't Saturate". Report. gzipped ps file
Mosheyev, L. and Zibulevsky, M. (1996). "Penalty/Barrier Multiplier Algorithm for Semidefinite Programming: Dual Bounds and Implementation". Research Report #1/96} , Optimization Laboratory.
Zibulevsky M. (1995) "New Penalty/Barrier and Lagrange Multiplier Approach for Semidefinite Programming". Research Report #5/95, Optimization Laboratory:
A. Ben-Tal, I. Yuzefovich, and M. Zibulevsky (1992). "Penalty/barrier multiplier methods for minimax and constrained smooth convex problems". Research Report 9/92, Optimization Laboratory, Faculty of Industrial Engineering and Management, Technion, Haifa, Israel.
Kuprienko, A. and Zibulevsky, M. (1987). " Efficient Data Transmission over High-noised Telephone Channels", NIIASS, Kiev, USSR.
Pointers to Other Pages
AMPL: A Modeling Language for Optimization
ICA - Independent Component Analysis
Some Bibliography on ICA and sparse decomposition
www.mathtools.net - Scientific computing links for MATLAB, C/C+, Fortran and others
NetLib: free numerical libraries
CONNECTIONISTS: neural computation mailing list
Book: Convex Optimization by Boyd and Vandenberghe
Slides to the book book Convex Optimization by Boyd and Vandenberghe
ICA page-papers,code,demo,links by Paris Smaragdis at MIT
ICA (independent component analysis by Allan Barros, Site in Japan )
ICA page of SALK Computational Neuroscience Laboratory
ICA CENTRAL: web page + mailing list (by Jean-François Cardoso)