Donald Goldfarb

According to our database1, Donald Goldfarb authored at least 88 papers between 1976 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 





ADMM for multiaffine constrained optimization.
Optimization Methods and Software, 2020

Practical Quasi-Newton Methods for Training Deep Neural Networks.
CoRR, 2020

Quasi-Newton methods: superlinear convergence without line searches for self-concordant functions.
Optimization Methods and Software, 2019

A Dynamic Sampling Adaptive-SGD Method for Machine Learning.
CoRR, 2019

Efficient Subsampled Gauss-Newton and Natural Gradient Methods for Training Neural Networks.
CoRR, 2019

Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Block BFGS Methods.
SIAM J. Optim., 2018

Greedy Approaches to Symmetric Orthogonal Tensor Decomposition.
SIAM J. Matrix Anal. Appl., 2017

Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization.
SIAM J. Optim., 2017

Using negative curvature in solving nonlinear programs.
Comput. Optim. Appl., 2017

Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values.
Proceedings of the 34th International Conference on Machine Learning, 2017

Linear Convergence of Stochastic Frank Wolfe Variants.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Scalable Robust Matrix Recovery: Frank-Wolfe Meets Proximal Methods.
SIAM J. Scientific Computing, 2016

Stochastic Block BFGS: Squeezing More Curvature out of Data.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Successive Rank-One Approximations for Nearly Orthogonally Decomposable Symmetric Tensors.
SIAM J. Matrix Anal. Appl., 2015

An alternating direction method for total variation denoising.
Optimization Methods and Software, 2015

Robust Low-Rank Tensor Recovery: Models and Algorithms.
SIAM J. Matrix Anal. Appl., 2014

Fast First-Order Methods for Composite Convex Optimization with Backtracking.
Found. Comput. Math., 2014

Efficient algorithms for robust and stable principal component pursuit problems.
Comput. Optim. Appl., 2014

Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery.
Proceedings of the 31th International Conference on Machine Learning, 2014

Efficient block-coordinate descent algorithms for the Group Lasso.
Math. Program. Comput., 2013

Fast alternating linearization methods for minimizing the sum of two convex functions.
Math. Program., 2013

Accelerated Linearized Bregman Method.
J. Sci. Comput., 2013

Fast Multiple-Splitting Algorithms for Convex Optimization.
SIAM J. Optim., 2012

On the convergence of an active-set method for ℓ1 minimization.
Optimization Methods and Software, 2012

Structured Sparsity via Alternating Direction Methods.
J. Mach. Learn. Res., 2012

Fixed point and Bregman iterative methods for matrix rank minimization.
Math. Program., 2011

An interior-point piecewise linear penalty method for nonlinear programming.
Math. Program., 2011

Convergence of Fixed-Point Continuation Algorithms for Matrix Rank Minimization.
Found. Comput. Math., 2011

Structured Sparsity via Alternating Directions Methods
CoRR, 2011

A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation.
SIAM J. Scientific Computing, 2010

Alternating direction augmented Lagrangian methods for semidefinite programming.
Math. Program. Comput., 2010

Sparse Inverse Covariance Selection via Alternating Linearization Methods.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Parametric Maximum Flow Algorithms for Fast Total Variation Minimization.
SIAM J. Scientific Computing, 2009

A Line Search Multigrid Method for Large-Scale Nonlinear Optimization.
SIAM J. Optim., 2009

A Curvilinear Search Method for p-Harmonic Flows on Spheres.
SIAM J. Imaging Sci., 2009

Bregman Iterative Algorithms for \ell1-Minimization with Applications to Compressed Sensing.
SIAM J. Imaging Sci., 2008

The Total Variation Regularized L1 Model for Multiscale Decomposition.
Multiscale Model. Simul., 2007

A comparison of three total variation based texture extraction models.
J. Vis. Commun. Image Represent., 2007

Interior-point l2-penalty methods for nonlinear programming with strong global convergence properties.
Math. Program., 2006

Second-order Cone Programming Methods for Total Variation-Based Image Restoration.
SIAM J. Scientific Computing, 2005

Product-form Cholesky factorization in interior point methods for second-order cone programming.
Math. Program., 2005

An Iterative Regularization Method for Total Variation-Based Image Restoration.
Multiscale Model. Simul., 2005

Image Cartoon-Texture Decomposition and Feature Selection Using the Total Variation Regularized L1 Functional.
Proceedings of the Variational, 2005

A product-form Cholesky factorization method for handling dense columns in interior point methods for linear programming.
Math. Program., 2004

Robust convex quadratically constrained programs.
Math. Program., 2003

Second-order cone programming.
Math. Program., 2003

Robust Portfolio Selection Problems.
Math. Oper. Res., 2003

Combinatorial interior point methods for generalized network flow problems.
Math. Program., 2002

A polynomial dual simplex algorithm for the generalized circulation problem.
Math. Program., 2002

A new scaling algorithm for the minimum cost network flow problem.
Oper. Res. Lett., 1999

An O(nm)-Time Network Simplex Algorithm for the Shortest Path Problem.
Oper. Res., 1999

A Modified Barrier-Augmented Lagrangian Method for Constrained Minimization.
Comput. Optim. Appl., 1999

Interior Point Trajectories in Semidefinite Programming.
SIAM J. Optim., 1998

Strongly polynomial dual simplex methods for the maximum flow problem.
Math. Program., 1998

On strongly polynomial dual simplex algorithms for the maximum flow problem.
Math. Program., 1997

Polynomial-Time Highest-Gain Augmenting Path Algorithms for the Generalized Circulation Problem.
Math. Oper. Res., 1997

A Faster Combinatorial Algorithm for the Generalized Circulation Problem.
Math. Oper. Res., 1996

On the Complexity of a Class of Projective Interior Point Methods.
Math. Oper. Res., 1995

Data-Parallel Implementations of Dense Simplex Methods on the Connection Machine CM-2.
INFORMS J. Comput., 1995

A Path-Following Projective Interior Point Method for Linear Programming.
SIAM J. Optim., 1994

Partial-Update Newton Methods for Unary, Factorable, and Partially Separable Optimization.
SIAM J. Optim., 1993

An O(n3L) primal-dual potential reduction algorithm for solving convex quadratic programs.
Math. Program., 1993

Exploiting special structure in a primal-dual path-following algorithm.
Math. Program., 1993

On the Maximum Capacity Augmentation Algorithm for the Maximum Flow Problem.
Discret. Appl. Math., 1993

Steepest-edge simplex algorithms for linear programming.
Math. Program., 1992

Polynomial-Time Primal Simplex Algorithms for the Minimum Cost Network Flow Problem.
Algorithmica, 1992

A Logarithmic Barrier Function Algorithm for Quadratically Constrained Convex Quadratic Programming.
SIAM J. Optim., 1991

On strongly polynomial variants of the network simplex algorithm for the maximum flow problem.
Oper. Res. Lett., 1991

Shortest path algorithms using dynamic breadth-first search.
Networks, 1991

A primal projective interior point method for linear programming.
Math. Program., 1991

An O(n3L) primal interior point algorithm for convex quadratic programming.
Math. Program., 1991

Anti-stalling pivot rules for the network simplex algorithm.
Networks, 1990

A Primal Simplex Algorithm that Solves the Maximum Flow Problem in at most nm Pivots and O(n2m) Time.
Math. Program., 1990

Efficient Shortest Path Simplex Algorithms.
Oper. Res., 1990

A relaxed version of Karmarkar's method.
Math. Program., 1988

Relaxed variants of Karmarkar's algorithm for linear programs with unknown optimal objective value.
Math. Program., 1988

Efficient dual simplex algorithms for the assignment problem.
Math. Program., 1986

A numerically stable dual method for solving strictly convex quadratic programs.
Math. Program., 1983

Modifications and implementation of the ellipsoid algorithm for linear programming.
Math. Program., 1982

Feature Article - The Ellipsoid Method: A Survey.
Oper. Res., 1981

Curvilinear path steplength algorithms for minimization which use directions of negative curvature.
Math. Program., 1980

Worst case behavior of the steepest edge simplex method.
Discret. Appl. Math., 1979

A practicable steepest-edge simplex algorithm.
Math. Program., 1977

Matrix factorizations in optimization of nonlinear functions subject to linear constraints - an addendum.
Math. Program., 1977

On the Bartels - Golub decomposition for linear programming bases.
Math. Program., 1977

Generating conjugate directions without line searches using factorized variable metric updating formulas.
Math. Program., 1977

Matrix factorizations in optimization of nonlinear functions subject to linear constraints.
Math. Program., 1976