A polynomial-time algorithm, based on Newton's method, for linear programming J Renegar Mathematical programming 40 (1), 59-93, 1988 | 855 | 1988 |
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 … J Renegar Journal of symbolic computation 13 (3), 255-299, 1992 | 839 | 1992 |
A mathematical view of interior-point methods in convex optimization J Renegar Society for Industrial and Applied Mathematics, 2001 | 672 | 2001 |
Linear programming, complexity theory and elementary functional analysis J Renegar Mathematical Programming 70 (1), 279-351, 1995 | 321 | 1995 |
Some perturbation theory for linear programming J Renegar Mathematical Programming 65 (3), 73-91, 1994 | 277 | 1994 |
Incorporating condition measures into the complexity theory of linear programming J Renegar SIAM Journal on Optimization 5 (3), 506-524, 1995 | 227 | 1995 |
Hyperbolic programs, and their derivative relaxations J Renegar Foundations of Computational Mathematics 6, 59-79, 2006 | 198 | 2006 |
On the worst-case arithmetic complexity of approximating zeros of polynomials J Renegar Journal of Complexity 3 (2), 90-113, 1987 | 170 | 1987 |
A faster PSPACE algorithm for deciding the existential theory of the reals J Renegar Cornell University Operations Research and Industrial Engineering, 1988 | 131 | 1988 |
On the computational complexity and geometry of the first-order theory of the reals. Part III: Quantifier elimination J Renegar Journal of Symbolic Computation 13 (3), 329-352, 1992 | 90 | 1992 |
On the worst-case arithmetic complexity of approximating zeros of systems of polynomials J Renegar SIAM Journal on Computing 18 (2), 350-370, 1989 | 83 | 1989 |
On the computational complexity and geometry of the first-order theory of the reals. Part II: The general decision problem. Preliminaries for quantifier elimination J Renegar Journal of Symbolic Computation 13 (3), 301-327, 1992 | 73 | 1992 |
On the efficiency of Newton's method in approximating all zeros of a system of complex polynomials J Renegar Mathematics of operations research 12 (1), 121-148, 1987 | 69 | 1987 |
Computing approximate solutions for convex conic systems of constraints J Pena, J Renegar Mathematical Programming 87, 351-383, 2000 | 64 | 2000 |
On the computational complexity of approximating solutions for real algebraic formulae J Renegar SIAM Journal on Computing 21 (6), 1008-1025, 1992 | 55 | 1992 |
Condition numbers, the barrier method, and the conjugate-gradient method J Renegar SIAM Journal on Optimization 6 (4), 879-912, 1996 | 53 | 1996 |
A simple nearly optimal restart scheme for speeding up first-order methods J Renegar, B Grimmer foundations of computational mathematics 22 (1), 211-256, 2022 | 52 | 2022 |
Is it possible to know a problem instance is ill-posed?: some foundations for a general theory of condition numbers J Renegar Journal of Complexity 10 (1), 1-56, 1994 | 47 | 1994 |
``Efficient” subgradient methods for general convex optimization J Renegar SIAM Journal on Optimization 26 (4), 2649-2676, 2016 | 43 | 2016 |
Efficient first-order methods for linear programming and semidefinite programming J Renegar arXiv preprint arXiv:1409.5832, 2014 | 38 | 2014 |