Guy Wolf, Ph.D.

Email: guy.wolf@cs.tau.ac.il

School of Computer Science
Tel-Aviv University
.

Major interests

  1. High-dimensional data analysis
  2. Dimensionality reduction
  3. Manifold learning
  4. Differential geometry
  5. Multiview approach for data analysis
  6. Nonlinear locally low dimensional geometries

List of Publications

  1. M. Salhov, A. Bermanis, G. Wolf, and A. Averbuch. Approximately-isometric diffusion maps. Applied and Computational Harmonic Analysis, 2014. DOI:10.1016/j.acha.2014.05.002.
  2. A. Bermanis, G. Wolf, and A. Averbuch. Cover-based bounds on the numerical rank of Gaussian kernels. Applied and Computational Harmonic Analysis, 36(2):302-315, 2014.
  3. A. Bermanis, G. Wolf, and A. Averbuch. Measure-based diffusion kernel methods. In SampTA 2013: 10th international conference on Sampling Theory and Applications, Bremen, Germany, 2013.
  4. M. Salhov, G. Wolf, A. Bermanis, and A. Averbuch. Constructive sampling for patch-based embedding. In SampTA 2013: 10th international conference on Sampling Theory and Applications, Bremen, Germany, 2013.
  5. G. Wolf and A. Averbuch. Linear-projection diffusion on smooth Euclidean submanifolds. Applied and Computational Harmonic Analysis, 34(1):1-14, 2013.
  6. G. Wolf, Y. Shmuelli, S. Harussi, and A. Averbuch. Polar classification of nominal data. In S. Repin, T. Tiihonen, and T. Tuovinen, editors, Numerical methods for differential equations, optimization, and technological problems, volume 27 of Computational Methods in Applied Sciences, pages 253-271, Springer Netherlands, 2013.
  7. M. Salhov, G. Wolf, A. Bermanis, A. Averbuch, and P. Neittaanmäki. Dictionary construction for patch-to-tensor embedding. In J. Hollmén, F. Klawonn, and A. Tucker, editors, Advances in Intelligent Data Analysis XI, volume 7619 of Lecture Notes in Computer Science, pages 346-356. Springer Berlin Heidelberg, 2012.
  8. M. Salhov, G. Wolf, A. Averbuch, and P. Neittaanmäki. Patch-based data analysis using linear-projection diffusion. In J. Hollmén, F. Klawonn, and A. Tucker, editors, Advances in Intelligent Data Analysis XI, volume 7619 of Lecture Notes in Computer Science, pages 334-345. Springer Berlin Heidelberg, 2012.
  9. G. Wolf, A. Rotbart, G. David, and A. Averbuch. Coarse-grained localized diffusion. Applied and Computational Harmonic Analysis, 33(3):388-400, 2012.
  10. Y. Shmueli, G. Wolf, and A. Averbuch. Updating kernel methods in spectral decomposition by affinity perturbations. Linear Algebra and its Applications, 437(6):1356-1365, 2012.
  11. M. Salhov, G. Wolf, and A. Averbuch. Patch-to-tensor embedding. Applied and Computational Harmonic Analysis, 33(2):182-203, 2012.
  12. G. Wolf, Y. Shmuelli, S. Harussi, and A. Averbuch. Polar clustering. In CAO2011: ECCOMAS Thematic Conference on Computational Analysis and Optimization, 2011.
  13. G. Wolf, A. Averbuch, and P. Neittaanmäki. Parameter Rating by Diffusion Gradient. In W. Fitzgibbon, Y.A. Kuznetsov, P. Neittaanmäki, O. Pironneau, editors, Modeling, Simulation and Optimization for Science and Technology, volume 34 of Computational Methods in Applied Sciences, In Press, Springer Netherlands, 2014.
  14. M. Salhov, A. Bermanis, G.Wolf, and A. Averbuch. Approximate patch-to-tensor embedding via dictionary construction. Submitted, 2012.
  15. A. Bermanis, G. Wolf, and A. Averbuch. Diffusion-based kernel methods on Euclidean metric measure spaces. Submitted, 2012.
  16. A. Bermanis, M. Salhov, G. Wolf, and A. Averbuch. Multiscale grid dictionary of locally low-dimensional geometries. In Preparation, 2013.