Publications

• A perturbation view of level-set methods for convex optimization
  R. Estrin, M. P. Friedlander
  arXiv:2001.06511, 2020  
• Polar alignment and atomic decomposition
  Z. Fan, H. Jeong, Y. Sun, M. P. Friedlander
  arXiv:1912.05068, 2019  
• Bundle methods for dual atomic pursuit
  Z. Fan, Y. Sun, M. P. Friedlander
  Asilomar Conf. Signals, Sytems, Computers (ACSSC), 2019  
• One-shot atomic detection
  Y. Sun, M. P. Friedlander
  IEEE Intern. Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019  
• Fast training for large-scale one-versus-all linear classifiers using tree-structured initialization
  H. Fang, M. Cheng, C.-J. Hsieh, M. P. Friedlander
  SIAM Intern. Conf. Data Mining (SDM19), 2019  
• Level-set methods for convex optimization
  A. Y. Aravkin, J. V. Burke, D. Drusvyatskiy, M. P. Friedlander, S. Roy
  Mathematical Programming, 174(1-2):359–390, 2019  
• Polar convolution
  M. P. Friedlander, I. Macêdo, T.K. Pong
  SIAM J. Optimization 29(2):1366–1391, 2019  
• Implementing a smooth exact penalty function for equality-constrained nonlinear optimization
  R. Estrin, M. P. Friedlander, D. Orban, M. A. Saunders
  arXiv:1910.04300, 2019  
• Implementing a smooth exact penalty function for constrained nonlinear optimization
  R. Estrin, M. P. Friedlander, D. Orban, M. A. Saunders
  arXiv:1912.02093, 2019  
• Smooth Structured Prediction Using Quantum and Classical Gibbs Samplers
  B. Sepehry, E. Iranmanesh, M. P. Friedlander, P. Ronagh
  arXiv:1809.04091, 2018  
• Foundations of gauge and perspective duality
  A. Y. Aravkin, J. V. Burke, D. Drusvyatskiy, M. P. Friedlander, K. MacPhee
  SIAM J. Optimization, 28(3):2406–2434, 2018  
• Efficient evaluation of scaled proximal operators
  M. P. Friedlander, G. Goh
  Electronic Trans. Numerical Analysis, 46:1–22, 2017  
• Satisfying Real-world Goals with Dataset Constraints
  G. Goh, A. Cotter, M. Gupta, M. P. Friedlander
  NIPS, 2016  
• Social Resistance
  M. P. Friedlander, N. Krislock, T. K. Pong
  IEEE Computing in Science and Engineering and Computing Edge, 2016  
• Low-rank spectral optimization via gauge duality
  M. P. Friedlander, I. Macêdo
  SIAM J. Scientific Computing, 38(3):A1616–A1638, 2016  
• Coordinate descent converges faster with the Gauss-Southwell rule than random selection
  J. Nutini, M. Schmidt, I. H. Laradji, M. P. Friedlander, H. Koepke
  Inter. Conf. Machine Learning (ICML), 2015  
• Gauge optimization and duality
  M. P. Friedlander, I. Macêdo, T. K. Pong
  SIAM J. Optimization, 24(4):1999–2022, 2014  
• Variational properties of value functions
  A. Aravkin, J. V. Burke, M. P. Friedlander
  SIAM J. Optimization, 23(3):1689–1717, 2013  
• Fast dual variational inference for non-conjugate latent gaussian models
  M. E. Khan, A. Y. Aravkin, M. P. Friedlander, M. Seeger
  ICML, 2013  
• Hybrid deterministic-stochastic methods for data fitting
  M. P. Friedlander, M. Schmidt
  SIAM J. Scientific Computing, 34(3):A1380–A1405, 2012  
• A primal-dual regularized interior-point method for convex quadratic programs
  M. P. Friedlander, D. Orban
  Mathematical Programming Computation, 4(1):71–107, 2012  
• Fighting the curse of dimensionality: compressive sensing in exploration seismology
  F. J. Herrmann, M. P. Friedlander, Ö. Yılmaz
  IEEE Signal Processing Magazine, 29(3):88–100, 2012  
• Robust inversion via semistochastic dimensionality reduction
  A. Aravkin, M. P. Friedlander, T. van Leeuwen
  ICASSP, 2012  
• Robust inversion, dimensionality reduction, and randomized sampling
  A. Aravkin, M. P. Friedlander, F. Herrmann, T. van Leeuwen
  Mathematical Programming, 134(1):101–125, 2012, 2012  
• Sparse optimization with least-squares constraints
  E. van den Berg, M. P. Friedlander
  SIAM J. Optimization, 21(4):1201–1229, 2011  
• Recovering compressively sampled signals using partial support information
  M. P. Friedlander, H. Mansour, R. Saab, Ö. Yılmaz
  IEEE Trans. Info. Theory, 58(2):1122–1134, 2011  
• Theoretical and empirical results for recovery from multiple measurements
  E. van den Berg, M. P. Friedlander
  IEEE Trans. Info. Theory, 56(5):2516–2527, 2011  
• Probing the Pareto frontier for basis pursuit solutions
  E. van den Berg, M. P. Friedlander
  SIAM J. Scientific Computing, 31(2):890–912, 2009  
• Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm
  M. Schmidt, E. van den Berg, M. P. Friedlander, K. Murphy
  Proc 12th Intern. Conf. AISTATS, 2009  
• Sparco: a testing framework for sparse reconstruction
  E. van den Berg, M. P. Friedlander, G. Hennenfent, F. Herrmann, R. Saab, Ö. Yılmaz
  ACM Trans. Math. Software, 35(4):1–16, 2009  
• Computing nonnegative tensor factorizations
  M. P. Friedlander, K. Hatz
  Optimization Methods and Software, 23(4):631–647, 2008  
• New insights into one-norm solvers from the Pareto curve
  G. Hennenfent, E. van den Berg, M. P. Friedlander, F. Herrmann
  Geophysics, 73(4):A23–A26, 2008  
• Global and finite termination of a two-phase augmented Lagrangian filter method for general quadratic programs
  M. P. Friedlander, S. Leyffer
  SIAM J. Scientific Computing, 30(4):1706–1726, 2008  
• Discussion: The Dantzig selector: Statistical estimation when p is much larger than n
  M. P. Friedlander, M. A. Saunders
  Annals of Statistics, 35(6):2385–2391, 2007  
• Exact regularization of convex programs
  M. P. Friedlander, P. Tseng
  SIAM J. Optimization, 18(4):1326–1350, 2007  
• A filter active-set trust-region method
  M. P. Friedlander, N. I. M. Gould, S. Leyffer, T. S. Munson
  Preprint ANL/MCS-P1456-0907, Argonne National Laboratory, 2007  
• In pursuit of a root
  E. van den Berg, M. P. Friedlander
  Tech. Rep. TR-2007-19, Dept. of Computer Science, UBC, 2007  
• Diffuse optical fluorescence tomography using time-resolved data acquired in transmission
  F. Leblond, S. Fortier, M. P. Friedlander
  Multimodal Biomedical Imaging II, vol. 6431. Proc. Intern. Society Optimal Imaging, 2007  
• On minimizing distortion and relative entropy
  M. P. Friedlander, M. R. Gupta
  IEEE Trans. Info. Theory, 52(1):238–245, 2006  
• A two-sided relaxation scheme for mathematical programs with equilibrium constraints
  V. Demiguel, M. P. Friedlander, F. J. Nogales, S. Scholtes
  SIAM J. Optimization, 16(1):587–609, 2005  
• A globally convergent linearly constrained Lagrangian method for nonlinear optimization
  M. P. Friedlander, M. A. Saunders
  SIAM J. Optimization 15(3), 863–897, 2005  
• Maximum entropy classification applied to speech
  M. R. Gupta, M. P. Friedlander, R. M. Gray
  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