James Renegar | Academic Influence

James Renegar's AcademicInfluence.com Rankings

James Renegar

Mathematics

#7608

World Rank

#10315

Historical Rank

Applied Mathematics

#435

World Rank

#466

Historical Rank

Measure Theory

#3319

World Rank

#3922

Historical Rank

mathematics Degrees

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Mathematics

James Renegar's Degrees

PhD Mathematics University of California, Berkeley
Masters Mathematics University of California, Berkeley
Bachelors Mathematics University of California, Berkeley

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Why Is James Renegar Influential?

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According to Wikipedia, James Milton Renegar Jr. is an American mathematician, specializing in optimization algorithms for linear programming and nonlinear programming. Biography In 1983 he received his Ph.D. in mathematics from the University of California, Berkeley. His Ph.D. thesis On the Computational Complexity of Simplicial Algorithms in Approximation Zeros of Complex Polynomials was supervised by Stephen Smale. After postdoc positions, Renegar joined in 1987 the faculty of the School of Operations Research and Information Engineering at Cornell University and is now a full professor there.

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James Renegar'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 mathematical view of interior-point methods in convex optimization (2001) (699)
A polynomial-time algorithm, based on Newton's method, for linear programming (1988) (567)
On the Computational Complexity and Geometry of the First-Order Theory of the Reals, Part I: Introduction. Preliminaries. The Geometry of Semi-Algebraic Sets. The Decision Problem for the Existential Theory of the Reals (1992) (423)
On the Computational Complexity and Geometry of the First-Order Theory of the Reals, Part I (1989) (365)
On the Computational Complexity and Geometry of the First-Order Theory of the Reals, Part III: Quantifier Elimination (1992) (266)
Linear programming, complexity theory and elementary functional analysis (1995) (265)
Some perturbation theory for linear programming (1994) (219)
Incorporating Condition Measures into the Complexity Theory of Linear Programming (1995) (197)
Hyperbolic Programs, and Their Derivative Relaxations (2006) (174)
On the worst-case arithmetic complexity of approximating zeros of polynomials (1987) (155)
A faster PSPACE algorithm for deciding the existential theory of the reals (1988) (81)
On the Worst-Case Arithmetic Complexity of Approximating Zeros of Systems of Polynomials (1989) (62)
On the Efficiency of Newton's Method in Approximating All Zeros of a System of Complex Polynomials (1987) (58)
On the Computational Complexity and Geometry of the First-Order Theory of the Reals, Part II: The General Decision Problem. Preliminaries for Quantifier Elimination (1992) (56)
Computing approximate solutions for convex conic systems of constraints (2000) (52)
On the Computational Complexity of Approximating Solutions for Real Algebraic Formulae (1992) (51)
Condition Numbers, the Barrier Method, and the Conjugate-Gradient Method (1996) (48)
Efficient First-Order Methods for Linear Programming and Semidefinite Programming (2014) (38)
Recent Progress on the Complexity of the Decision Problem for the Reals (1990) (34)
"Efficient" Subgradient Methods for General Convex Optimization (2016) (32)
The mathematics of numerical analysis (1996) (32)
Is It Possible to Know a Problem Instance Is Ill-Posed?: Some Foundations for a General Theory of Condition Numbers (1994) (30)
A Simple Nearly Optimal Restart Scheme For Speeding Up First-Order Methods (2018) (30)
Unified complexity analysis for Newton LP methods (1992) (26)
On the cost of approximating all roots of a complex polynomial (1985) (24)
The mathematics of numerical analysis : 1995 AMS-SIAM Summer Seminar in Applied Mathematics, July 17-August 11, 1995, Park City, Utah (1996) (23)
Accelerated first-order methods for hyperbolic programming (2015) (23)
A Framework for Applying Subgradient Methods to Conic Optimization Problems (2015) (17)
On the complexity of a piecewise linear algorithm for approximating roots of complex polynomials (1985) (13)
Rudiments of an average case complexity theory for piecewise-linear path following algorithms (1988) (12)
A Polynomial-Time Affine-Scaling Method for Semidefinite and Hyperbolic Programming (2014) (12)
Central Swaths (A Generalization of the Central Path) (2010) (8)
Towards a computational complexity theory that uses approximate data and knowledge (1993) (3)
Ill-Posed Problem Instances (1993) (2)
Central Swaths (2010) (2)
Notes on the Efficiency of the Barrier Method (1993) (1)
Accelerated first-order methods for hyperbolic programming (2017) (1)
A Different Perspective On The Stochastic Convex Feasibility Problem (2021) (1)
A Simple Nearly Optimal Restart Scheme For Speeding Up First-Order Methods (2021) (0)
Foreword (2005) (0)
3. Conic Programming and Duality (2001) (0)
A framework for applying subgradient methods (2019) (0)
2. Basic Interior-Point Method Theory (2001) (0)
Central Swaths (2013) (0)
Foreword (2015) (0)
Foreword (2015) (0)

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