Michael P. Friedlander

According to our database, Michael P. Friedlander authored at least 54 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Cardinality-constrained structured data-fitting problems.

Zhenan Fan, Huang Fang, Michael P. Friedlander

Open J. Math. Optim., 2024

Fair and Efficient Contribution Valuation for Vertical Federated Learning.

Zhenan Fan, Huang Fang, Xinglu Wang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Yong Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

From Perspective Maps to Epigraphical Projections.

Michael P. Friedlander, Ariel Goodwin, Tim Hoheisel

Math. Oper. Res., August, 2023

2022

Polar Deconvolution of Mixed Signals.

Zhenan Fan, Halyun Jeong, Babhru Joshi, Michael P. Friedlander

IEEE Trans. Signal Process., 2022

NBIHT: An Efficient Algorithm for 1-Bit Compressed Sensing With Optimal Error Decay Rate.

Michael P. Friedlander, Halyun Jeong, Yaniv Plan, Özgür Yilmaz

IEEE Trans. Inf. Theory, 2022

Quantum algorithms for structured prediction.

Behrooz Sepehry, Ehsan Iranmanesh, Michael P. Friedlander, Pooya Ronagh

Quantum Mach. Intell., 2022

Online Mirror Descent and Dual Averaging: Keeping Pace in the Dynamic Case.

Huang Fang, Nicholas J. A. Harvey, Victor S. Portella, Michael P. Friedlander

J. Mach. Learn. Res., 2022

Knowledge-Injected Federated Learning.

Zhenan Fan, Zirui Zhou, Jian Pei, Michael P. Friedlander, Jiajie Hu, Chengliang Li, Yong Zhang

CoRR, 2022

A dual approach for federated learning.

Zhenan Fan, Huang Fang, Michael P. Friedlander

CoRR, 2022

Fair and efficient contribution valuation for vertical federated learning.

Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Yong Zhang

CoRR, 2022

Improving Fairness for Data Valuation in Horizontal Federated Learning.

Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021

Improving Fairness for Data Valuation in Federated Learning.

Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang

CoRR, 2021

Fast convergence of stochastic subgradient method under interpolation.

Huang Fang, Zhenan Fan, Michael P. Friedlander

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Implementing a Smooth Exact Penalty Function for General Constrained Nonlinear Optimization.

Ron Estrin, Michael P. Friedlander, Dominique Orban, Michael A. Saunders

SIAM J. Sci. Comput., 2020

Implementing a Smooth Exact Penalty Function for Equality-Constrained Nonlinear Optimization.

Ron Estrin, Michael P. Friedlander, Dominique Orban, Michael A. Saunders

SIAM J. Sci. Comput., 2020

A perturbation view of level-set methods for convex optimization.

Ron Estrin, Michael P. Friedlander

Optim. Lett., 2020

Atomic Decomposition via Polar Alignment: The Geometry of Structured Optimization.

Zhenan Fan, Halyun Jeong, Yifan Sun, Michael P. Friedlander

Found. Trends Optim., 2020

Greed Meets Sparsity: Understanding and Improving Greedy Coordinate Descent for Sparse Optimization.

Huang Fang, Zhenan Fan, Yifan Sun, Michael P. Friedlander

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Polar Convolution.

Michael P. Friedlander, Ives Macêdo, Ting Kei Pong

SIAM J. Optim., 2019

Level-set methods for convex optimization.

Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy

Math. Program., 2019

Polar Alignment and Atomic Decomposition.

Zhenan Fan, Halyun Jeong, Yifan Sun, Michael P. Friedlander

CoRR, 2019

Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization.

Huang Fang, Minhao Cheng, Cho-Jui Hsieh, Michael P. Friedlander

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

One-shot atomic detection.

Yifan Sun, Michael P. Friedlander

Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

Bundle methods for dual atomic pursuit.

Zhenan Fan, Yifan Sun, Michael P. Friedlander

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

Foundations of Gauge and Perspective Duality.

Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Kellie J. MacPhee

SIAM J. Optim., 2018

Smooth Structured Prediction Using Quantum and Classical Gibbs Samplers.

Behrooz Sepehry, Ehsan Iranmanesh, Michael P. Friedlander, Pooya Ronagh

CoRR, 2018

2016

Low-Rank Spectral Optimization via Gauge Duality.

Michael P. Friedlander, Ives Macêdo

SIAM J. Sci. Comput., 2016

Social Resistance.

Michael P. Friedlander, Nathan Krislock, Ting Kei Pong

Comput. Sci. Eng., 2016

Efficient evaluation of scaled proximal operators.

Michael P. Friedlander, Gabriel Goh

CoRR, 2016

Satisfying Real-world Goals with Dataset Constraints.

Gabriel Goh, Andrew Cotter, Maya R. Gupta, Michael P. Friedlander

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Low-rank spectral optimization.

Michael P. Friedlander, Ives Macêdo

CoRR, 2015

Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection.

Julie Nutini, Mark Schmidt, Issam H. Laradji, Michael P. Friedlander, Hoyt A. Koepke

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Gauge Optimization and Duality.

Michael P. Friedlander, Ives Macêdo, Ting Kei Pong

SIAM J. Optim., 2014

2013

Erratum: Hybrid Deterministic-Stochastic Methods for Data Fitting.

Michael P. Friedlander, Mark Schmidt

SIAM J. Sci. Comput., 2013

Variational Properties of Value Functions.

Aleksandr Y. Aravkin, James V. Burke, Michael P. Friedlander

SIAM J. Optim., 2013

Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models.

Mohammad Emtiyaz Khan, Aleksandr Y. Aravkin, Michael P. Friedlander, Matthias W. Seeger

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Recovering Compressively Sampled Signals Using Partial Support Information.

Michael P. Friedlander, Hassan Mansour, Rayan Saab, Özgür Yilmaz

IEEE Trans. Inf. Theory, 2012

Fighting the Curse of Dimensionality: Compressive Sensing in Exploration Seismology.

Felix J. Herrmann, Michael P. Friedlander, Özgür Yilmaz

IEEE Signal Process. Mag., 2012

Hybrid Deterministic-Stochastic Methods for Data Fitting.

Michael P. Friedlander, Mark Schmidt

SIAM J. Sci. Comput., 2012

A primal-dual regularized interior-point method for convex quadratic programs.

Michael P. Friedlander, Dominique Orban

Math. Program. Comput., 2012

Robust inversion, dimensionality reduction, and randomized sampling.

Aleksandr Y. Aravkin, Michael P. Friedlander, Felix J. Herrmann, Tristan van Leeuwen

Math. Program., 2012

Robust inversion via semistochastic dimensionality reduction.

Aleksandr Y. Aravkin, Michael P. Friedlander, Tristan van Leeuwen

Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011

Sparse Optimization with Least-Squares Constraints.

Ewout van den Berg, Michael P. Friedlander

SIAM J. Optim., 2011

2010

Theoretical and empirical results for recovery from multiple measurements.

Ewout van den Berg, Michael P. Friedlander

IEEE Trans. Inf. Theory, 2010

2009

Algorithm 890: Sparco: A Testing Framework for Sparse Reconstruction.

Ewout van den Berg, Michael P. Friedlander, Gilles Hennenfent, Felix J. Herrmann, Rayan Saab, Özgür Yilmaz

ACM Trans. Math. Softw., 2009

Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm.

Mark Schmidt, Ewout van den Berg, Michael P. Friedlander, Kevin P. Murphy

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Joint-sparse recovery from multiple measurements

Ewout van den Berg, Michael P. Friedlander

CoRR, 2009

2008

Global and Finite Termination of a Two-Phase Augmented Lagrangian Filter Method for General Quadratic Programs.

Michael P. Friedlander, Sven Leyffer

SIAM J. Sci. Comput., 2008

Probing the Pareto Frontier for Basis Pursuit Solutions.

Ewout van den Berg, Michael P. Friedlander

SIAM J. Sci. Comput., 2008

Computing non-negative tensor factorizations.

Michael P. Friedlander, Kathrin Hatz

Optim. Methods Softw., 2008

2007

Exact Regularization of Convex Programs.

Michael P. Friedlander, Paul Tseng

SIAM J. Optim., 2007

2006

On minimizing distortion and relative entropy.

Michael P. Friedlander, M. R. Gupta

IEEE Trans. Inf. Theory, 2006

2005

A Globally Convergent Linearly Constrained Lagrangian Method for Nonlinear Optimization.

Michael P. Friedlander, Michael A. Saunders

SIAM J. Optim., 2005

A two-sided relaxation scheme for Mathematical Programs with Equilibrium Constraints.

Victor DeMiguel, Michael P. Friedlander, Francisco J. Nogales, Stefan Scholtes

SIAM J. Optim., 2005