Donald Goldfarb | Academic Influence

Donald Goldfarb's AcademicInfluence.com Rankings

Donald Goldfarb

Mathematics

#1762

World Rank

#2823

Historical Rank

#718

USA Rank

Operations Research

#12

World Rank

#12

Historical Rank

#8

USA Rank

Measure Theory

#1065

World Rank

#1369

Historical Rank

#390

USA Rank

mathematics Degrees

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Mathematics

Donald Goldfarb's Degrees

PhD Operations Research Stanford University
Masters Operations Research Stanford University
Bachelors Mathematics City College of New York

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Why Is Donald Goldfarb Influential?

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According to Wikipedia, Donald Goldfarb is an American mathematician, best known for his works in mathematical optimization and numerical analysis. Biography Goldfarb studied Chemical Engineering at Cornell University, earning a BSChE in 1963. He obtained an M.S. from Princeton University in 1965, and a doctorate in 1966.

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Donald Goldfarb's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

A family of variable-metric methods derived by variational means (1970) (2507)
An Iterative Regularization Method for Total Variation-Based Image Restoration (2005) (1824)
Second-order cone programming (2003) (1579)
Bregman Iterative Algorithms for \ell1-Minimization with Applications to Compressed Sensing (2008) (1499)
Fixed point and Bregman iterative methods for matrix rank minimization (2009) (1065)
A numerically stable dual method for solving strictly convex quadratic programs (1983) (1006)
Robust Portfolio Selection Problems (2003) (905)
The Ellipsoid Method: A Survey (1980) (426)
Alternating direction augmented Lagrangian methods for semidefinite programming (2010) (403)
Robust Low-Rank Tensor Recovery: Models and Algorithms (2013) (339)
Fast alternating linearization methods for minimizing the sum of two convex functions (2009) (282)
A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation (2010) (280)
Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery (2013) (277)
Feature Article - The Ellipsoid Method: A Survey (1981) (275)
Steepest-edge simplex algorithms for linear programming (1992) (223)
Second-order Cone Programming Methods for Total Variation-Based Image Restoration (2005) (220)
A practicable steepest-edge simplex algorithm (1977) (211)
Efficient block-coordinate descent algorithms for the Group Lasso (2013) (205)
Extension of Davidon’s Variable Metric Method to Maximization Under Linear Inequality and Equality Constraints (1969) (204)
Sparse Inverse Covariance Selection via Alternating Linearization Methods (2010) (201)
Convergence of Fixed-Point Continuation Algorithms for Matrix Rank Minimization (2009) (155)
An O(n3L) primal interior point algorithm for convex quadratic programming (1991) (146)
Stochastic Block BFGS: Squeezing More Curvature out of Data (2016) (138)
Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization (2014) (138)
Robust convex quadratically constrained programs (2003) (137)
Image Cartoon-Texture Decomposition and Feature Selection Using the Total Variation Regularized L1 Functional (2005) (135)
The Total Variation Regularized L1 Model for Multiscale Decomposition (2007) (120)
Fast Multiple-Splitting Algorithms for Convex Optimization (2009) (116)
Parametric Maximum Flow Algorithms for Fast Total Variation Minimization (2009) (115)
Interior-point ℓ2-penalty methods for nonlinear programming with strong global convergence properties (2006) (104)
A computational comparison of the dinic and network simplex methods for maximum flow (1988) (103)
Dual and primal-dual methods for solving strictly convex quadratic programs (1982) (100)
Interior Point Trajectories in Semidefinite Programming (1998) (91)
Curvilinear path steplength algorithms for minimization which use directions of negative curvature (1980) (84)
Worst case behavior of the steepest edge simplex method (1979) (80)
Structured Sparsity via Alternating Direction Methods (2011) (78)
Fast First-Order Methods for Composite Convex Optimization with Backtracking (2014) (74)
Conjugate Gradient Method for Nonlinear Programming Problems with Linear Constraints (1968) (73)
Provable Models for Robust Low-Rank Tensor Completion (2015) (73)
Accelerated Linearized Bregman Method (2011) (72)
A comparison of three total variation based texture extraction models (2007) (70)
Scalable Robust Matrix Recovery: Frank-Wolfe Meets Proximal Methods (2014) (67)
On the convergence of an active-set method for ℓ1 minimization (2012) (65)
Block Coordinate Descent Methods for Semidefinite Programming (2012) (64)
Factorized variable metric methods for unconstrained optimization (1976) (57)
Polynomial-Time Highest-Gain Augmenting Path Algorithms for the Generalized Circulation Problem (1997) (56)
A primal simplex algorithm that solves the maximum flow problem in at mostnm pivots and O(n2m) time (1990) (55)
A Curvilinear Search Method for p-Harmonic Flows on Spheres (2009) (54)
Provable Low-Rank Tensor Recovery (2014) (52)
On parametric semidefinite programming (1999) (51)
Practical Quasi-Newton Methods for Training Deep Neural Networks (2020) (51)
Modifications and implementation of the ellipsoid algorithm for linear programming (1982) (49)
An alternating direction method for total variation denoising (2011) (48)
A Faster Combinatorial Algorithm for the Generalized Circulation Problem (1996) (43)
A Line Search Multigrid Method for Large-Scale Nonlinear Optimization (2009) (43)
A Modified Barrier-Augmented Lagrangian Method for Constrained Minimization (1999) (42)
On the Bartels—Golub decomposition for linear programming bases (1977) (42)
Efficient algorithms for robust and stable principal component pursuit problems (2013) (42)
Optimal estimation of Jacobian and Hessian matrices that arise in finite difference calculations (1984) (41)
Efficient dual simplex algorithms for the assignment problem (1986) (39)
Efficient Shortest Path Simplex Algorithms (1990) (39)
Data-Parallel Implementations of Dense Simplex Methods on the Connection Machine CM-2 (1995) (37)
Total Variation Based Image Cartoon-Texture Decomposition (2005) (36)
ROW BY ROW METHODS FOR SEMIDEFINITE PROGRAMMING (2009) (36)
Quasi-Newton methods: superlinear convergence without line searches for self-concordant functions (2016) (36)
ADMM for multiaffine constrained optimization (2018) (35)
A relaxed version of Karmarkar's method (1988) (35)
A polynomial dual simplex algorithm for the generalized circulation problem (2002) (33)
Fast First-Order Methods for Stable Principal Component Pursuit (2011) (30)
Exploiting special structure in a primal—dual path-following algorithm (1993) (27)
Successive Rank-One Approximations for Nearly Orthogonally Decomposable Symmetric Tensors (2015) (26)
Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values (2017) (26)
A product-form Cholesky factorization method for handling dense columns in interior point methods for linear programming (2004) (25)
Product-form Cholesky factorization in interior point methods for second-order cone programming (2005) (25)
Solving low-rank matrix completion problems efficiently (2009) (24)
Relaxed variants of Karmarkar's algorithm for linear programs with unknown optimal objective value (1988) (23)
Shortest path algorithms using dynamic breadth-first search (1991) (22)
Modification Methods for Inverting Matrices and Solving Systems of Linear Algebraic Equations (1972) (22)
Linear Convergence of Stochastic Frank Wolfe Variants (2017) (22)
Anti-stalling pivot rules for the network simplex algorithm (1990) (21)
On the Complexity of the Simplex Method (1994) (21)
Chapter II Linear programming (1989) (18)
USING THE STEEPEST-EDGE SIMPLEX ALGORITHM TO SOLVE SPARSE LINEAR PROGRAMS (1976) (18)
On strongly polynomial variants of the network simplex algorithm for the maximum flow problem (1991) (18)
Block BFGS Methods (2016) (17)
Matrix factorizations in optimization of nonlinear functions subject to linear constraints (1976) (17)
An O(nm)-Time Network Simplex Algorithm for the Shortest Path Problem (1999) (17)
Efficient Subsampled Gauss-Newton and Natural Gradient Methods for Training Neural Networks (2019) (17)
Unbiased Simulation for Optimizing Stochastic Function Compositions (2017) (17)
Robust Active Portfolio Management (2008) (17)
Using negative curvature in solving nonlinear programs (2017) (17)
A primal projective interior point method for linear programming (1991) (17)
A Logarithmic Barrier Function Algorithm for Quadratically Constrained Convex Quadratic Programming (1991) (17)
Partial-Update Newton Methods for Unary, Factorable, and Partially Separable Optimization (1993) (14)
AN ACTIVE SET METHOD FOR MATHEMATICAL PROGRAMS WITH LINEAR COMPLEMENTARITY CONSTRAINTS (2007) (14)
A LINE SEARCH MULTIGRID METHOD FOR LARGE-SCALE CONVEX OPTIMIZATION (2007) (14)
An O(n3L) primal—dual potential reduction algorithm for solving convex quadratic programs (1993) (14)
Kronecker-factored Quasi-Newton Methods for Convolutional Neural Networks (2021) (14)
Variable metric and conjugate direction methods in unconstrained optimization: recent developments (1972) (14)
Combinatorial interior point methods for generalized network flow problems (2002) (13)
Efficient dual simplex algorithms for the assignment problem (1985) (13)
Greedy Approaches to Symmetric Orthogonal Tensor Decomposition (2017) (13)
Polynomial-time primal simplex algorithms for the minimum cost network flow problem (1992) (12)
Fixed point and Bregman iterative methods for matrix rank (2009) (12)
Increasing Iterate Averaging for Solving Saddle-Point Problems (2019) (12)
Strongly polynomial dual simplex methods for the maximum flow problem (1998) (11)
A Path-Following Projective Interior Point Method for Linear Programming (1994) (11)
An interior-point piecewise linear penalty method for nonlinear programming (2011) (11)
A self-correcting version of Karmarkar's algorithm (1989) (10)
Algorithms for sparse and low-rank optimization: convergence, complexity and applications (2011) (10)
A new scaling algorithm for the minimum cost network flow problem (1999) (10)
On strongly polynomial dual simplex algorithms for the maximum flow problem (1997) (10)
Modifications and Implementation of the Shor-Khachian Algorithm for Linear Programming (1980) (9)
Square Deal : Lower Bounds and Improved Convex Relaxations for Tensor Recovery (2015) (9)
Solving Structured Convex Quadratic Programs by Interior Point Methods with Application to Support Vector Machines and Portfolio Optimization ∗ (2005) (8)
TR-2004-11 Robust Portfolio Management (2004) (7)
Generating conjugate directions without line searches using factorized variable metric updating formulas (1977) (7)
Tensor Normal Training for Deep Learning Models (2021) (7)
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models (2019) (7)
Numerically stable LDLT factorizations in interior point methods for convex quadratic programming (2008) (6)
The Use of Negative Curvature in Minimization Algorithms (1980) (6)
Intellectual Disability Etiologies and Associated Psychiatric Disorders (2007) (3)
On solution-containing ellipsoids in linear programming (1994) (3)
Efficient primal algorithms for strictly convex quadratic programs (1986) (3)
On the Complexity of a Class of Projective Interior Point Methods (1995) (3)
A Mini-Block Natural Gradient Method for Deep Neural Networks (2022) (2)
The Mathematical Programming Society (1977) (2)
CORC Technical Report TR-2002-03 Robust portfolio selection problems (2002) (2)
Fast alternating linearization methods for minimizing the sum of two convex functions (2012) (1)
Algorithms for Nonlinear Programming. (1983) (1)
On the Maximum Capacity Augmentation Algorithm for the Maximum Flow Problem (1993) (1)
A Dynamic Sampling Adaptive-SGD Method for Machine Learning (2019) (1)
Semi-Stochastic Frank-Wolfe Algorithms with Away-Steps for Block-Coordinate Structure Problems (2016) (1)
Algorithms for the generalized network flow problem (2001) (1)
Random Walk Distributed Dual Averaging Method For Decentralized Consensus Optimization (2015) (1)
Kronecker-factored Quasi-Newton Methods for Deep Learning (2021) (1)
Matrix factorizations in optimization of nonlinear functions subject to linear constraints — an addendum (1977) (1)
Accelerated Linearized Bregman Method (2012) (0)
Efficient block-coordinate descent algorithms for the Group Lasso (2013) (0)
Steepest Edge Algorithms in Linear and Nonlinear Programming. (1980) (0)
Using negative curvature in solving nonlinear programs (2017) (0)
An Adaptive Mini-Block Fisher Method for Deep Neural Networks (2022) (0)
TR-2002-04 Robust convex quadratically constrained programs ∗ (2002) (0)
The Mathematical Programming Society (1972) (0)
Algorithms for Mathematical Programming with Emphasis on Bi-level Models (2014) (0)
Efficient algorithms for robust and stable principal component pursuit problems (2013) (0)
Fast First-Order Methods for Composite Convex Optimization with Backtracking (2014) (0)
The Mathematical Programming Society (1976) (0)
TR-2004-11 Robust Active Portfolio Management ∗ (2008) (0)
Algorithms for solving some structured mathematical programs (1992) (0)
Symposia lectures (2007) (0)
MetPetDB: New Directions for Metamorphic Studies (2008) (0)
The Mathematical Programming Society (1978) (0)
RICE UNIVERSITY CAAM TECHNICAL REPORT TR06-16 THE TOTAL VARIATION REGULARIZED L MODEL FOR MULTISCALE DECOMPOSITION (2006) (0)
A Mini-Block Fisher Method for Deep Neural Networks (2022) (0)
Supplementary Material : Linear Convergence of Stochastic Frank Wolfe Variants (2017) (0)
The tv-l(1) model: theory, computation, and applications (2006) (0)
RWDDA : Distributed Dual Averaging Made Practical (2017) (0)

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