I'm a Math+X postdoctoral fellow, working with Emmanuel Candes at Stanford University. I received my Ph.D. in Electrical Engineering and Computer Science from UC Berkeley in 2016. My Ph.D. advisors were Martin Wainwright and Laurent El Ghaoui, and my studies were supported partially by a Microsoft Research PhD Fellowship.

Research Interests: Large Scale Optimization, Machine Learning and Big Data, Signal Processing, Compressed Sensing, Information Theory and Polar Coding

Contact

Email:
pilanci[at]stanford.edu
mert[at]berkeley.edu
Address:
450 Serra Mall, Bldg 380
Stanford University
Stanford, CA 94305

Publications

2015

M. Pilanci and M. J. Wainwright
Newton Sketch: A Linear-time Optimization Algorithm with Linear-Quadratic Convergence
submitted to SIAM Journal of Optimization, arXiv preprint arXiv:1505.02250, 2015
randomized algorithms newton's method interior point method convex optimization linear program logistic regression
arXiv
M. Pilanci and M. J. Wainwright
Iterative Hessian sketch: Fast and accurate solution approximation for constrained least-squares
Journal of Machine Learning Research (JMLR) 17, 2016
information-theoretic lower-bounds sketching l1 regularized least-squares nuclear norm regularization
arXiv PDF
M. Pilanci, M. J. Wainwright, and L. E. Ghaoui
Sparse learning via Boolean relaxations
Mathematical Programming, 151(1), 2015
sparse regression sparse classification randomized rounding
DOI, PDF
M. Pilanci and M.J. Wainwright
Randomized Sketches of Convex Programs With Sharp Guarantees
IEEE Transactions on Information Theory, 61(9), 2015
random projection regression compressed sensing data privacy
DOI, arXiv
Y. Yang, M. Pilanci, and M. J. Wainwright
Randomized sketches for kernels: Fast and optimal non-parametric regression
accepted to Annals of Statistics 2015
kernel regression smoothing random projection Rademacher complexity
arXiv

2014

M. Pilanci and M. J. Wainwright
Randomized sketches of convex programs with sharp guarantees
2014 IEEE International Symposium on Information Theory (ISIT), , 2014
DOI, arXiv
random projection convex optimization

2012

M. Pilanci, L. E. Ghaoui, and V. Chandrasekaran
Recovery of sparse probability measures via convex programming
Advances in Neural Information Processing Systems (NIPS), 2012
PDF
probability measures convex relaxation data clustering

A. C. Gurbuz, M. Pilanci, and O. Arikan
Expectation maximization based matching pursuit
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on, 2012
DOI, PDF
sparse approximation compressed sensing

2011

A. C. Gurbuz, M. Pilanci, and O. Arikan
Sparse signal reconstruction with ellipsoid enlargement
Signal Processing and Communications Applications (SIU), 2011 IEEE 19th Conference on, 2011
DOI
M. Pilanci and O. Arikan
Recovery of sparse perturbations in least squares problems
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on, 2011
DOI

2010

M. Pilanci, O. Arikan, and E. Arikan
Polar compressive sampling: A novel technique using Polar codes
Signal Processing and Communications Applications Conference (SIU), 2010 IEEE 18th, 2010
B. Guldogan, M. Pilanci, and O. Arikan
Compressed sensing on ambiguity function domain for high resolution detection
Signal Processing and Communications Applications Conference (SIU), 2010 IEEE 18th, 2010
M. Pilanci and O. Arikan
Compressive sampling and adaptive multipath estimation
Signal Processing and Communications Applications Conference (SIU), 2010 IEEE 18th, 2010
M. Pilanci, O. Arikan, and M. C. Pinar
Structured least squares problems and robust estimators
Signal Processing, IEEE Transactions on, 58(5), 2010
DOI

2009

M. Pilanci, O. Arikan, B. Oguz, and M. Pinar
A novel technique for a linear system of equations applied to channel equalization
Signal Processing and Communications Applications Conference, 2009. SIU 2009. IEEE 17th, 2009
DOI
M. Pilanci, O. Arikan, B. Oguz, and M. Pinar
Structured least squares with bounded data uncertainties
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on, 2009
DOI