Publications

• Z. Fan, H. Jeong, Y. Sun, M. P. Friedlander. Polar alignment and atomic decomposition. arXiv:1912.05068, 2019
• Z. Fan, Y. Sun, M. P. Friedlander. Bundle methods for dual atomic pursuit. arXiv:1910.13650, 2019
• Y. Sun, M. P. Friedlander. One-shot atomic detection. IEEE Intern. Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019
• H. Fang, M. Cheng, C.-J. Hsieh, M. P. Friedlander. Fast training for large-scale one-versus-all linear classifiers using tree-structured initialization. SIAM Intern. Conf. Data Mining (SDM19), 2019
• A. Y. Aravkin, J. V. Burke, D. Drusvyatskiy, M. P. Friedlander, S. Roy. Level-set methods for convex optimization. Mathematical Programming, 174(1-2):359–390, 2019
• M. P. Friedlander, I. Macêdo, T.K. Pong. Polar convolution. SIAM J. Optimization 29(2):1366–1391, 2019
• R. Estrin, M. P. Friedlander, D. Orban, M. A. Saunders. Implementing a smooth exact penalty function for equality-constrained nonlinear optimization. arXiv:1910.04300, 2019
• R. Estrin, M. P. Friedlander, D. Orban, M. A. Saunders. Implementing a smooth exact penalty function for constrained nonlinear optimization. arXiv:1912.02093, 2019
• B. Sepehry, E. Iranmanesh, M. P. Friedlander, P. Ronagh. Smooth Structured Prediction Using Quantum and Classical Gibbs Samplers. 2018
• A. Y. Aravkin, J. V. Burke, D. Drusvyatskiy, M. P. Friedlander, K. MacPhee. Foundations of gauge and perspective duality. SIAM J. Optimization, 28(3):2406–2434, 2018
• R. Estrin, M. P. Friedlander. A perturbation view of level-set methods for convex optimization. 2018
• M. P. Friedlander, G. Goh. Efficient evaluation of scaled proximal operators. Electronic Trans. Numerical Analysis, 46:1–22, 2017
• G. Goh, A. Cotter, M. Gupta, M. P. Friedlander. Satisfying Real-world Goals with Dataset Constraints. NIPS, 2016
• M. P. Friedlander, N. Krislock, T. K. Pong. Social Resistance. IEEE Computing in Science and Engineering and Computing Edge, 2016
• M. P. Friedlander, I. Macêdo. Low-rank spectral optimization via gauge duality. SIAM J. Scientific Computing, 38(3):A1616–A1638, 2016
• J. Nutini, M. Schmidt, I. H. Laradji, M. P. Friedlander, H. Koepke. Coordinate descent converges faster with the Gauss-Southwell rule than random selection. ICML, 2015
• M. P. Friedlander, I. Macêdo, T. K. Pong. Gauge optimization and duality. SIAM J. Optimization, 24(4):1999–2022, 2014
• A. Aravkin, J. V. Burke, M. P. Friedlander. Variational properties of value functions. SIAM J. Optimization, 23(3):1689–1717, 2013
• M. E. Khan, A. Y. Aravkin, M. P. Friedlander, M. Seeger. Fast dual variational inference for non-conjugate latent gaussian models. ICML, 2013
• M. P. Friedlander, M. Schmidt. Hybrid deterministic-stochastic methods for data fitting. SIAM J. Scientific Computing, 34(3):A1380–A1405, 2012
• M. P. Friedlander, D. Orban. A primal-dual regularized interior-point method for convex quadratic programs. Mathematical Programming Computation, 4(1):71–107, 2012
• F. J. Herrmann, M. P. Friedlander, Ö. Yılmaz. Fighting the curse of dimensionality: compressive sensing in exploration seismology. IEEE Signal Processing Magazine, 29(3):88–100, 2012
• A. Aravkin, M. P. Friedlander, T. van Leeuwen. Robust inversion via semistochastic dimensionality reduction. ICASSP, 2012
• A. Aravkin, M. P. Friedlander, F. Herrmann, T. van Leeuwen. Robust inversion, dimensionality reduction, and randomized sampling. Mathematical Programming, 134(1):101–125, 2012, 2012
• E. van den Berg, M. P. Friedlander. Sparse optimization with least-squares constraints. SIAM J. Optimization, 21(4):1201–1229, 2011
• M. P. Friedlander, H. Mansour, R. Saab, Ö. Yılmaz. Recovering compressively sampled signals using partial support information. IEEE Trans. Info. Theory, 58(2):1122–1134, 2011
• E. van den Berg, M. P. Friedlander. Theoretical and empirical results for recovery from multiple measurements. IEEE Trans. Info. Theory, 56(5):2516–2527, 2011
• E. van den Berg, M. P. Friedlander. Probing the Pareto frontier for basis pursuit solutions. SIAM J. Scientific Computing, 31(2):890–912, 2009
• M. Schmidt, E. van den Berg, M. P. Friedlander, K. Murphy. Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm. Proc 12th Intern. Conf. AISTATS, 2009
• E. van den Berg, M. P. Friedlander, G. Hennenfent, F. Herrmann, R. Saab, Ö. Yılmaz. Sparco: a testing framework for sparse reconstruction. ACM Trans. Math. Software, 35(4):1–16, 2009
• M. P. Friedlander, K. Hatz. Computing nonnegative tensor factorizations. Optimization Methods and Software, 23(4):631–647, 2008
• G. Hennenfent, E. van den Berg, M. P. Friedlander, F. Herrmann. New insights into one-norm solvers from the Pareto curve. Geophysics, 73(4):A23–A26, 2008
• M. P. Friedlander, S. Leyffer. Global and finite termination of a two-phase augmented Lagrangian filter method for general quadratic programs. SIAM J. Scientific Computing, 30(4):1706–1726, 2008
• M. P. Friedlander, M. A. Saunders. Discussion: The Dantzig selector: Statistical estimation when p is much larger than n. Annals of Statistics, 35(6):2385–2391, 2007
• M. P. Friedlander, P. Tseng. Exact regularization of convex programs. SIAM J. Optimization, 18(4):1326–1350, 2007
• M. P. Friedlander, N. I. M. Gould, S. Leyffer, T. S. Munson. A filter active-set trust-region method. Preprint ANL/MCS-P1456-0907, Argonne National Laboratory, 2007
• E. van den Berg, M. P. Friedlander. In pursuit of a root. Tech. Rep. TR-2007-19, Dept. of Computer Science, UBC, 2007
• F. Leblond, S. Fortier, M. P. Friedlander. Diffuse optical fluorescence tomography using time-resolved data acquired in transmission. Multimodal Biomedical Imaging II, vol. 6431. Proc. Intern. Society Optimal Imaging, 2007
• M. P. Friedlander, M. R. Gupta. On minimizing distortion and relative entropy. IEEE Trans. Info. Theory, 52(1):238–245, 2006
• V. Demiguel, M. P. Friedlander, F. J. Nogales, S. Scholtes. A two-sided relaxation scheme for mathematical programs with equilibrium constraints. SIAM J. Optimization, 16(1):587–609, 2005
• M. P. Friedlander, M. A. Saunders. A globally convergent linearly constrained Lagrangian method for nonlinear optimization. SIAM J. Optimization 15(3), 863–897, 2005
• M. R. Gupta, M. P. Friedlander, R. M. Gray. Maximum entropy classification applied to speech. 34th Asilomar Conf. Signals, Systems and Computers, vol. 2, 1480–1483, 2000

Selected Talks

• Polar Duality in three liftings, McGill University, Montreal. November 28, 2017
• Algorithms for sparse optimization, Google Research, Mountain View. May 19, 2015
• Robust inversion and randomized sampling, International Symposium on Mathematical Programming (ISMP), Berlin. August 23, 2012