Michael P. Friedlander

Orcid: 0000-0003-0222-5222

Affiliations:
  • University of British Columbia, Department of Computer Science, Vancouver, BC, Canada


According to our database1, Michael P. Friedlander authored at least 52 papers between 2005 and 2023.

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Bibliography

2023
From Perspective Maps to Epigraphical Projections.
Math. Oper. Res., August, 2023

2022
Polar Deconvolution of Mixed Signals.
IEEE Trans. Signal Process., 2022

NBIHT: An Efficient Algorithm for 1-Bit Compressed Sensing With Optimal Error Decay Rate.
IEEE Trans. Inf. Theory, 2022

Quantum algorithms for structured prediction.
Quantum Mach. Intell., 2022

Online Mirror Descent and Dual Averaging: Keeping Pace in the Dynamic Case.
J. Mach. Learn. Res., 2022

Knowledge-Injected Federated Learning.
CoRR, 2022

A dual approach for federated learning.
CoRR, 2022

Fair and efficient contribution valuation for vertical federated learning.
CoRR, 2022

Improving Fairness for Data Valuation in Horizontal Federated Learning.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021
Improving Fairness for Data Valuation in Federated Learning.
CoRR, 2021

Fast convergence of stochastic subgradient method under interpolation.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Implementing a Smooth Exact Penalty Function for General Constrained Nonlinear Optimization.
SIAM J. Sci. Comput., 2020

Implementing a Smooth Exact Penalty Function for Equality-Constrained Nonlinear Optimization.
SIAM J. Sci. Comput., 2020

A perturbation view of level-set methods for convex optimization.
Optim. Lett., 2020

Atomic Decomposition via Polar Alignment: The Geometry of Structured Optimization.
Found. Trends Optim., 2020

Greed Meets Sparsity: Understanding and Improving Greedy Coordinate Descent for Sparse Optimization.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Polar Convolution.
SIAM J. Optim., 2019

Level-set methods for convex optimization.
Math. Program., 2019

Polar Alignment and Atomic Decomposition.
CoRR, 2019

Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

One-shot atomic detection.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

Bundle methods for dual atomic pursuit.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
Foundations of Gauge and Perspective Duality.
SIAM J. Optim., 2018

Smooth Structured Prediction Using Quantum and Classical Gibbs Samplers.
CoRR, 2018

2016
Low-Rank Spectral Optimization via Gauge Duality.
SIAM J. Sci. Comput., 2016

Social Resistance.
Comput. Sci. Eng., 2016

Efficient evaluation of scaled proximal operators.
CoRR, 2016

Satisfying Real-world Goals with Dataset Constraints.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Low-rank spectral optimization.
CoRR, 2015

Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Gauge Optimization and Duality.
SIAM J. Optim., 2014

2013
Erratum: Hybrid Deterministic-Stochastic Methods for Data Fitting.
SIAM J. Sci. Comput., 2013

Variational Properties of Value Functions.
SIAM J. Optim., 2013

Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Recovering Compressively Sampled Signals Using Partial Support Information.
IEEE Trans. Inf. Theory, 2012

Fighting the Curse of Dimensionality: Compressive Sensing in Exploration Seismology.
IEEE Signal Process. Mag., 2012

Hybrid Deterministic-Stochastic Methods for Data Fitting.
SIAM J. Sci. Comput., 2012

A primal-dual regularized interior-point method for convex quadratic programs.
Math. Program. Comput., 2012

Robust inversion, dimensionality reduction, and randomized sampling.
Math. Program., 2012

Robust inversion via semistochastic dimensionality reduction.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011
Sparse Optimization with Least-Squares Constraints.
SIAM J. Optim., 2011

2010
Theoretical and empirical results for recovery from multiple measurements.
IEEE Trans. Inf. Theory, 2010

2009
Algorithm 890: Sparco: A Testing Framework for Sparse Reconstruction.
ACM Trans. Math. Softw., 2009

Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Joint-sparse recovery from multiple measurements
CoRR, 2009

2008
Global and Finite Termination of a Two-Phase Augmented Lagrangian Filter Method for General Quadratic Programs.
SIAM J. Sci. Comput., 2008

Probing the Pareto Frontier for Basis Pursuit Solutions.
SIAM J. Sci. Comput., 2008

Computing non-negative tensor factorizations.
Optim. Methods Softw., 2008

2007
Exact Regularization of Convex Programs.
SIAM J. Optim., 2007

2006
On minimizing distortion and relative entropy.
IEEE Trans. Inf. Theory, 2006

2005
A Globally Convergent Linearly Constrained Lagrangian Method for Nonlinear Optimization.
SIAM J. Optim., 2005

A two-sided relaxation scheme for Mathematical Programs with Equilibrium Constraints.
SIAM J. Optim., 2005


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