These reports can be downloaded in either compressed postscript or pdf format by clicking on the appropriate tag.

- linear.pdf. (OK)

R.D.C. Monteiro, I. Adler, “An O ( n^3 L ) primal-dual interior point algorithm for linear programming”.

Revised version: “Interior path following primal-dual algorithms. Part I: Linear programming,”*Mathematical Programming*44 (1989) 27-41. - quad.pdf. (OK)

R.D.C. Monteiro, I. Adler, “An O ( n^3 L ) interior point algorithm for convex quadratic programming”.

Revised version: “Interior path following primal-dual algorithms. Part II: Convex quadratic programming,”*Mathematical Programming*44 (1989) 43-66. - nonli.pdf. (OK)

R.D.C. Monteiro, I. Adler, “An extension of Karmarkar type algorithm to a class of convex separable programming problems with global linear rate of convergence,”*Mathematics of Operations Research*15 (1990) 408-422. - pd.pdf. (OK)

R.D.C. Monteiro, I. Adler and M.G.C. Resende, “A polynomial-time primal-dual affine scaling algorithm for linear and convex quadratic programming and its power series extension,”*Mathematics of Operations Research*15 (1990) 191-214. - waffine.pdf. (OK)

I. Adler and R.D.C. Monteiro, “Limiting behavior of the affine scaling continuous trajectories for linear programming problems,”*Mathematical Programming*50 (1991) 29-51. It also appeared in: J.C. Lagarias and M.J. Todd, eds.*Contemporary Mathematics: Proceedings of the AMS-IMS-SIAM Joint Summer Research Conference on “Mathematical Developments Arising from Linear Programming,”*(Providence, Rhode Island, 1990) pp. 189-211. - projective.pdf. (OK)

R.D.C. Monteiro, “Convergence and boundary behavior of the projective scaling trajectories for linear programming,”*Mathematics of Operations Research*16 (1991) 842-858. It also appeared in: J.C. Lagarias and M.J. Todd, eds.*Contemporary Mathematics: Proceedings of the AMS-IMS-SIAM Joint Summer Research Conference on “Mathematical Developments Arising from Linear Programming,”*Providence, Rhode Island, 1990, pp 213-229. - sensi.pdf. (OK)

I. Adler and R.D.C. Monteiro, “A geometric view of parametric linear programming,”*Algorithmica*8 (1992) 161-176. - potential.pdf. (OK)

R.D.C. Monteiro, “On the continuous trajectories for a potential reduction algorithm for linear programming,”*Mathematics of Operations Research*17 (1992) 225-253. - convex.pdf. (OK)

R.D.C. Monteiro, “A globally convergent primal-dual interior point algorithm for convex programming,”*Mathematical Programming*64 (1994) 123-147. - primconv1.

R.D.C. Monteiro, “The global convergence of a class of primal potential reduction algorithms for convex programming,” manuscript, SIE Dept., University of Arizona, Tucson, AZ 85721, 1991 (submitted to*SIAM Journal on Optimization*). - range.pdf. (OK)

R.D.C. Monteiro and S. Mehrotra, “A General Parametric Analysis Approach and Its Implication to Sensitivity Analysis in Interior Point Methods,”*Mathematical Programming*72 (1996) 65-82. - paper.ps.

R.D.C. Monteiro and S. Wright, “A globally and superlinearly convergent potential reduction interior point method for convex programming,” SIE Working Paper 92-13, SIE Department, University of Arizona, Tucson, AZ 85721, 1992 (submitted to*SIAM Journal on Optimization*). - aff.pdf. (OK)

R.D.C. Monteiro, T. Tsuchiya and Y. Wang, “A simplified global convergence proof of the affine scaling algorithm,”*Annals of Operations Research*47 (1993) 443-482. - supaff.pdf. (OK)

T. Tsuchiya and R.D.C. Monteiro, “Superlinear convergence of the affine scaling algorithm,”*Mathematical Programming*75 (1996) 77-110. - lcp.pdf. (OK)

R.D.C. Monteiro and T. Tsuchiya, “Limiting behavior of the derivatives of certain trajectories associated with a monotone horizontal linear complementarity problem,”*Mathematics of Operations Research*21 (1996) 793-814. - positive.pdf. (OK)

R.D.C. Monteiro, J.-S. Pang, and T. Wang, “A Positive Algorithm for the Nonlinear Complementarity Problem,”*SIAM Journal on Optimization*5 (1995) 129-148. - jne.pdf. (OK)

R.D.C. Monteiro and S. Wright: “Local convergence of interior-point algorithms for degenerate monotone LCPs,”*Computational Optimization and Applications*3 (1993) 131-155. - fas.pdf. (OK)

R.D.C. Monteiro and S. Wright: “Superlinear primal-dual affine scaling algorithms for LCP,”*Mathematical Programming*69 (1995) 311-333. - ias.pdf. (OK)

R.D.C. Monteiro and S. Wright: “A superlinear infeasible-interior-point affine scaling algorithm for LCP,”*SIAM Journal on Optimization*6 (1996) 1-18. - gncp.pdf. (OK)

R.D.C. Monteiro and J.-S. Pang: “Properties of an interior-point mapping for mixed complementarity problems,”*Mathematics of Operations Research*21 (1996) 629-654. - nle.ps, nle.pdf. (OK)

T. Wang, R.D.C. Monteiro and J.–S. Pang, “An interior point potential reduction method for constrained equations,”*Mathematical Programming*74 (1996) 159-195. - cp.pdf. (OK)

R.D.C. Monteiro and F. Zhou, “On the Existence and Convergence of the Central Path for Convex Programming and Some Duality Results,”*Computational Optimization and Applications*10 (1998) 51-77. - pdeg.pdf. (OK)

Y. Wang and R.D.C. Monteiro, “Nondegeneracy of polyhedra and linear programs,”*Computational Optimization and Applications*7 (1997) 221-237. - quadaff.ps, quadaff.pdf. (OK)

R.D.C. Monteiro and T. Tsuchiya: “Global convergence of the affine scaling algorithm for convex quadratic programming,”*SIAM Journal on Optimization*8 (1998) 26-58. - supconv.pdf. (OK)

R.D.C. Monteiro and F. Zhou: ” On Superlinear Convergence of Infeasible-Interior-Point Algorithms for Linearly Constrained Convex Programs,”*Computational Optimization and Applications*8 (1997) 245-262. - trust.pdf. (OK)

R.D.C. Monteiro and Y. Wang: ” Trust Region Affine Scaling Algorithms for Linearly Constrained Convex and Concave Programs,”*Mathematical Programming*80 (1998) 283-313. - sdp.ps, sdp.pdf. (OK)

R.D.C. Monteiro: ” Primal-Dual Path-Following Algorithms for Semidefinite Programming,”*SIAM Journal on Optimization*7 (1997) 663-678. - gsncp.pdf. (OK)

R.D.C. Monteiro and Jong-Shi Pang: ” On Two Interior-Point Mappings for Nonlinear Semidefinite Complementarity Problems,”*Mathematics of Operations Research*23 (1998) 39-60. - zhang.pdf. (OK)

R.D.C. Monteiro and Y. Zhang: ” A Unified Analysis for a Class of Path-Following Primal-Dual Interior-Point Algorithms for Semidefinite Programming,”*Mathematical Programming*81 (1998) 281-299. - note.pdf. (OK)

R.D.C. Monteiro and P. Zanjacomo: ” A Note on the Existence of the Alizadeh-Haeberly-Overton Direction for Semidefinite Programming,”*Mathematical Programming*78 (1997) 393-396. - aho.ps, aho.pdf. (OK)

R.D.C. Monteiro: “Polynomial Convergence of Primal-Dual Algorithms for Semidefinite Programming Based on Monteiro and Zhang Family of Directions,”*SIAM Journal on Optimization*8 (1998) 797-812. - ksh.ps, ksh.pdf. (OK)

R.D.C. Monteiro and T. Tsuchiya: ” Polynomiality of Primal-Dual Algorithms for Semidefinite Linear Complementarity Problem Based on the Kojima-Shindoh-Hara Family of Directions,”*Mathematical Programming*, 84 (1999) 39-53. - mtfam.ps, mtfam.pdf. (OK)

R.D.C. Monteiro and T. Tsuchiya, “Polynomial Convergence of a New Family of Primal-Dual Algorithms for Semidefinite Programming,”*SIAM Journal on Optimization*9 (1999) 551-577. - nlesdp.pdf. (OK)

R.D.C. Monteiro and J.-S. Pang, “A Potential Reduction Newton Method for Constrained Equations,”*SIAM Journal on Optimization*9 (1999) 729-754. - dir5.ps.

R.D.C. Monteiro and P. Zanjacomo, “Implementation of Primal-Dual Methods for Semidefinite Programming Based on Monteiro and Tsuchiya Newton Directions and their Variants,”*Optimization Methods and Software*11/12 (1999) 91-140. - iusem.pdf. (OK)

A. Iusem and R.D.C. Monteiro, “On Dual Convergence of the Generalized Proximal Point Method with Bregman Distances,”*Mathematics of Operations Research*25 (2000) 606-624. - maps.pdf. (OK)

R.D.C. Monteiro and P. Zanjacomo: “General Interior-Point Maps and Existence of Weighted Paths for Nonlinear Semidefinite Complementarity Problems,”*Mathematics of Operations Research*25 (2000) 381-399. - ahoice.ps, ahoice.pdf. (OK)

R.D.C. Monteiro and T. Tsuchiya: “Polynomial Convergence of Primal-Dual Algorithms for the Second-Order Cone Program Based on the MZ-Family of Directions,”*Mathematical Programming*88 (2000) 61-83. - maxcut.ps, maxcut.pdf.

S. Burer and R.D.C. Monteiro: “A Projected Gradient Algorithm for Solving the Maxcut SDP Relaxation,”*Optimization Methods and Software*15 (2001) 175-200.K) - unify.pdf. (OK)

S. Burer and R.D.C. Monteiro: “A General Framework for Establishing Polynomial Convergence of Long-Step Methods for Semidefinite Programming”,*Optimization Methods and Software*18 (2003) 1-38. - transf.ps.

S. Burer, R.D.C. Monteiro and Y. Zhang: “Solving Semidefinite Programs via Nonlinear Programming. Part I: Transformations and Derivatives”, working paper, School of ISyE, Georgia Tech, USA, September 1999 (submitted to*Mathematical Programming*). - nlint.ps.

S. Burer, R.D.C. Monteiro and Y. Zhang: “Solving Semidefinite Programs via Nonlinear Programming. Part II: Interior Point Methods for a Subclass of SDPs”, working paper, School of ISyE, Georgia Tech, USA, October 1999 (submitted to*Mathematical Programming*). - a) transf.ps, transf.pdf. (OK) (This is a revised version of the papers 41 and 42 which have been merged to form the present paper.)

S. Burer, R.D.C. Monteiro and Y. Zhang: “Solving a class of semidefinite programs via nonlinear programming”,*Mathematical Programming*, 93 (2002) 97-122. - gnlint.pdf. (OK)

S. Burer, R.D.C. Monteiro and Y. Zhang: “Interior-Point Algorithms for Semidefinite Programming Based on A Nonlinear Programming Formulation”,*Computational Optimization and Applications*22 (2002) 49-79. - r2mcut.ps, r2mcut.pdf. (OK)

S. Burer, R.D.C. Monteiro and Y. Zhang: “Rank-Two Relaxation Heuristics for Max-Cut and Other Binary Quadratic Programs”,*SIAM Journal on Optimization*12 (2002) 503-521. - stabset.ps, stable.pdf. (OK)

S. Burer, R.D.C. Monteiro and Y. Zhang: “Maximum stable set formulations and heuristics based on continuous optimization”,*Mathematical Programming*94 (2002) 137-166. - lowrank.ps, lowrank.pdf. (OK)

S. Burer and R.D.C. Monteiro: “A nonlinear programming algorithm for solving semidefinite programs via low-rank factorization”,*Mathematical Programming, Series B*95 (2003) 329-357. - layered.pdf. (OK)

R.D.C. Monteiro and T. Tsuchiya: “A variant of the Vavasis-Ye layered-step interior-point algorithm for linear programming”,*SIAM Journal on Optimization*13 (2003) 1054-1079. - dualimpl.ps, dualimpl.pdf. (OK)

S. Burer, R.D.C. Monteiro and Y. Zhang: “A computational study of a gradient-based log-barrier algorithm for a class of large-scale SDPs”,*Mathematical Programming, Series B*95 (2003) 359-379. - layaff.ps, layaff.pdf. (OK)

R.D.C. Monteiro and T. Tsuchiya: “A new iteration-complexity bound for the MTY predictor-corrector algorithm”,*SIAM Journal on Optimization*15 (2004) 319-347. - sdptut.pdf. (OK)

R.D.C. Monteiro: “First- and second-order methods for semidefinite programming”,*Mathematical Programming, Series B*97 (2003) 209-244. - precond.ps, precond.pdf. (OK)

R.D.C. Monteiro, J.W. O’Neal and T. Tsuchiya: “Uniform boundedness of a preconditioned normal matrix used in interior point methods”,*SIAM Journal on Optimization*15 (2004) 96-100. - wpath.ps. wpath.pdf. (OK)

Z. Lu and R.D.C. Monteiro: “Error bounds and limiting behavior of weighted paths associated with the SDP map $X^{1/2}SX^{1/2}$”,*SIAM Journal on Optimization*15 (2004) 348-374. - centralpath.pdf. (OK)

J.X. da Cruz Neto, O. P. Ferreira and R.D.C. Monteiro: “Asymptotic behavior of the central path for a special class of degenerate SDP problems”,*Mathematical Programming*103 (2005) 487-514. - limaho.pdf. (OK)

Z. Lu and R.D.C. Monteiro: “Limiting behavior of the Alizadeh-Haeberly-Overton weighted paths in semidefinite programming”,*Optimization Methods and Software*22 (2007) 849-870. - lr.pdf (OK)

S. Burer and R.D.C. Monteiro: “Local minima and convergence in low-rank semidefinite programming”,*Mathematical Programming*103 (2005) 427-444. - lprecond.ps, lprecond.pdf.

R.D.C. Monteiro and J.W. O’Neal: “Convergence analysis of a long-step primal-dual infeasible interior-point LP algorithm based on iterative linear solvers”, working paper, School of ISyE, Georgia Tech, USA, October 2003 (submitted to*Mathematical Programming*). - bregman.ps, bregman.pdf. (OK)

J.X. da Cruz Neto, O.P. Ferreira, A.N. Iusem and R.D.C. Monteiro: “Dual convergence of the proximal point method with Bregman distances for linear programming”,*Optimization Methods and Software*22 (2007) 339-360. - notekoj.ps, notekoj.pdf. (OK)

Z. Lu and R.D.C. Monteiro: “A note on the local convergence of a predictor-corrector interior-point algorithm for the semidefinite linear complementarity problem based on the {Alizadeh-Haeberly-Overton} search direction”,*SIAM Journal on Optimization*15 (2005) 1147–1154. - qpprecond.pdf. (OK)

Z. Lu, R.D.C. Monteiro and J.W. O’Neal: “An iterative solver-based infeasible primal-dual path-following algorithm for convex quadratic programming”,*SIAM Journal on Optimization*17 (2006) 287-310. - tr.pdf. (OK)

Z. Lu and R.D.C. Monteiro: “A modified nearly exact method for solving low-rank trust region subproblem”,*Mathematical Programming*109 (2007) 385-411. - cg.ps, cg.pdf.

R.D.C. Monteiro, J.W. O’Neal and A. Nemirovski: “A new conjugate gradient algorithm incorporating adaptive ellipsoid preconditioning”, working paper, School of ISyE, Georgia Tech, USA, October 2004 (submitted to*SIAM Journal on Optimization*). - pmirror.pdf. (OK)

Z. Lu, R.D.C. Monteiro and A. Nemirovski: “Large-scale semidefinite programming via saddle point mirror-prox algorithm”,*Mathematical Programming*109 (2007) 211-237. - gqpprecond.pdf. (OK)

Z. Lu, R.D.C. Monteiro and J. O’Neal: “An Iterative Solver-Based Long-Step Infeasible Primal-Dual Path-Following Algorithm for Convex QP Based on a Class of Preconditioners”,*Optimization Methods and Software*24 (2009) 123-143. - curv.pdf. (OK)

Z. R.D.C. Monteiro and T. Tsuchiya: “A strong bound on the integral of the central path curvature and its relationship with the iteration complexity of primal-dual path-following LP algorithms”,*Mathematical Programming*115 (2008) 105-149. - multridge.pdf. (OK)

M. Yuan, A. Ekici, Z. Lu and R.D.C. Monteiro: “Dimension Reduction and Coefficient Estimation in the Multivariate Linear Regression”,*Journal of the Royal Statistical Society, Series B*69 (2007) 329-346. - pdfirst.pdf. (OK)

G. Lan, Z. Lu and R.D.C. Monteiro: “Primal-dual first-order methods with ${\cal O}(1/\epsilon)$ iteration-complexity for cone programming”,*Mathematical Programming*126 (2011) 1-29. - pctr.pdf. (OK)

G. Lan, R.D.C. Monteiro and T. Tsuchiya: “A polynomial predictor-corrector trust-region algorithm for linear programming”,*SIAM Journal on Optimization*19 (2009) 1918-1946. - dimreduct.pdf. (OK)

Z. Lu, R.D.C. Monteiro and M. Yuan: “Convex optimization methods for dimension reduction and coefficient estimation in multivariate linear regression”,*Mathematical Programming*131 (2012) 163-194. - penalty.pdf. (OK)

G. Lan and R.D.C. Monteiro: “Iteration-complexity of first-order penalty methods for convex programming”,*Mathematical Programming*138 (2013) 115-139. - benar.pdf. (OK)

R.D.C. Monteiro and B.F. Svaiter: “On the complexity of the hybrid proximal extragradient method for the iterates and the ergodic mean”,*SIAM Journal on Optimization*20 (2010) 2755-2787. - aug_lag.pdf. (OK)

G. Lan and R.D.C. Monteiro: “Iteration-complexity of first-order augmented Lagrangian methods for convex programming”,*Mathematical Programming*155 (2016) 511-547. - sparsePCA.pdf.

Y. He, R.D.C. Monteiro and H. Park: “An efficient algorithm for single sparse PCA”, working paper, School of ISyE, Georgia Tech, USA, June 2010 (submitted to*Proceedings of the Conference on Neural Information Processing Systems(NIPS)*). - genkorp.pdf. (OK)

R.D.C. Monteiro and B.F. Svaiter: “Complexity of variants of Tseng’s modified F-B splitting and Korpelevich’s methods for hemi-variational inequalities with applications to saddle point and convex optimization problems”,*SIAM Journal on Optimization*21 (2011) 1688-1720. - block-decom.pdf. (OK)

R.D.C. Monteiro and B.F. Svaiter: “Iteration-complexity of block-decomposition algorithms and the alternating direction method of multipliers”,*SIAM Journal on Optimization*23 (2013) 475-507. - gradient.ps, gradient.pdf.

R.D.C. Monteiro and B.F. Svaiter: “Convergence rate of inexact proximal point methods with relative error criteria for convex optimization”, working paper, School of ISyE, Georgia Tech, USA, August 2010 (submitted to*SIAM Journal on Optimization*). - newton-prox.pdf. (OK)

R.D.C. Monteiro and B.F. Svaiter: “Iteration-complexity of a Newton proximal extragradient method for monotone variational inequalities and inclusion problems”,*SIAM Journal on Optimization*22 (2012) 914-935. - prox-accel.pdf. (OK)

R.D.C. Monteiro and B.F. Svaiter: “An accelerated hybrid proximal extragradient method for convex optimization and its implications to second-order methods”,*SIAM Journal on Optimization*23 (2013) 1092-1125. - ImplementationBD.pdf. (OK)

R.D.C. Monteiro, C. Ortiz and B.F. Svaiter: “Implementation of a block-decomposition algorithm for solving large-scale conic semidefinite programming problems”,*Computational Optimization and Applications*57 (2014) 45-69. - 2EBD-HPE.pdf. (OK)

R.D.C. Monteiro, C. Ortiz and B.F. Svaiter: “A first-order block-decomposition method for solving two-easy-block structured semidefinite programs”,*Mathematical Programming Computation*6 (2014) 103-150. - AA_method.pdf. (OK)

R.D.C. Monteiro, C. Ortiz and B.F. Svaiter: “An adaptive accelerated first-order method for convex optimization”,*Computational Optimization and Applications*64 (2016) 31-73; DOI: 10.1007/s10589-015-9802-0. - sc-hpe.pdf. (OK)

R.D.C. Monteiro, M.R. Sicre and B.F. Svaiter: “A hybrid proximal extragradient self-concordant primal barrier method for monotone variational inequalities”,*SIAM Journal on Optimization*25 (2015) 1965-1996. - saddle_v4.pdf. (OK)

Y. He and R.D.C. Monteiro: “Accelerating block-decomposition first-order methods for solving composite saddle-point and two-player Nash equilibrium problems”,*SIAM Journal on Optimization*25 (2015) 2182-2211. - CC-ISBD.pdf.

R.D.C. Monteiro, C. Ortiz and B. F. Svaiter: “An inexact block-decomposition method for extra large-scale conic semidefinite programming” working paper, School of ISyE, Georgia Tech, USA, December 2013. - bilinear_v5.pdf. (OK)

Y. He and R.D.C. Monteiro: “An accelerated HPE-type algorithm for a class of composite convex-concave saddle-point problems”,*SIAM Journal on Optimization 26*(2016) 29-56. - maicon.pdf.

M. Marques Alves, R.D.C. Monteiro and B. F. Svaiter: “Primal-dual regularized SQP and SQCQP type methods for convex programming and their complexity analysis”, working paper, School of ISyE, Georgia Tech, USA, May 2014. - stm_bmr.pdf. (OK)

M. Marques Alves, R.D.C. Monteiro and B. F. Svaiter: “Regularized HPE-type methods for solving monotone inclusions with improved pointwise iteration-complexity bounds”,*SIAM Journal on Optimization*26 (2016) 2730-2743. - oliver.pdf. (OK)

O. Kolossoski and R.D.C. Monteiro: “An accelerated non-Euclidean hybrid proximal extragradient-type algorithm for convex-concave saddle-point problems”,*Optimization Methods and Software*32 (2017) 1244-1272. (DOI: 10.1080/10556788.2016.1266355) - rj-atlanta.pdf. (OK)

M. Marques Alves, R.D.C. Monteiro and B. F. Svaiter: “Iteration-complexity of a Rockafellar’s proximal method of multipliers for convex programming based on second-order approximations”,*Optimization*68 (2019) 1521-1550 (https://doi.org/10.1080/02331934.2019.1597357) - RE-NE-HPE.pdf. (OK)

M.L.N. Goncalves, J.G. Melo and R.D.C. Monteiro: “Improved pointwise iteration-complexity of a regularized ADMM and of a regularized non-Euclidean HPE framework”,*SIAM Journal on Optimization*27 (2017) 379-407 (DOI: 10.1137/16M1055530). - DR.pdf. (OK)

R.D.C. Monteiro and C.-K. Sim: “Complexity of the relaxed Peaceman-Rachford splitting method for the sum of two maximal strongly monotone operators”,*Computational Optimization and Applications*70 (2018) 763-790. - Ergodic-NE-HPE.pdf. (OK)

M.L.N. Goncalves, J.G. Melo and R.D.C. Monteiro: “On the iteration-complexity of a non-Euclidean hybrid proximal extragradient framework and of a proximal ADMM”,*Optimization 69 (2020) 847-873*(https://doi.org/10.1080/02331934.2019.1652297). - two-block-theta.pdf. (OK)

M.L.N. Goncalves, J.G. Melo and R.D.C. Monteiro: “Convergence rate bounds for a proximal ADMM with over-relaxation stepsize parameter for solving nonconvex linearly constrained problems”,*Pacific Journal of Optimization*15 (2019) 379-398. - multi-block-linearized.pdf.

J.G. Melo and R.D.C. Monteiro: “Iteration-Complexity of a Linearized Proximal Multiblock ADMM Class for Linearly Constrained Nonconvex Optimization Problems”, working paper, April 14, 2017. - multi-block-jacobi.pdf.

J.G. Melo and R.D.C. Monteiro, “Iteration-complexity of Jacobi-type non-Euclidean ADMM for multi-block linearly constrained nonconvex programs”, working paper, May 13 , 2017. - nonconvex-penalty-accelerated-ipp.pdf. (OK)

W. Kong, J. G. Melo and R.D.C. Monteiro, ”Complexity of a quadratic penalty accelerated inexact proximal point method for solving linearly constrained nonconvex composite programs”,*SIAM Journal on Optimization*29 (2019) 2566-2593 (https://doi.org/10.1137/18M1171011). - nonconvex-adaptive-accelerated-ipp.pdf. (OK)

W. Kong, J. G. Melo and R.D.C. Monteiro, ”An efficient adaptive accelerated inexact proximal point method for solving linearly constrained nonconvex composite problems”, Computational Optimization and its Applications 76 (2020) 305-346 (https://doi.org/10.1007/s10589-020-00188-w). - nonconvex-doubly-accelerated-composite-gradient.pdf.

J. Liang and R.D.C. Monteiro, ”A Doubly Accelerated Inexact Proximal Point Method for Nonconvex Composite Optimization Problems”, working paper, December 2018 (submitted to SIAM Journal on Optimization). - nonconvex-fista-acg.pdf. (OK)

J. Liang, R.D.C. Monteiro and C.-K. Sim, ”A FISTA-type accelerated gradient algorithm for solving smooth nonconvex composite optimization problems”,*Computational Optimization and its Applications*79 (2021) 649-679 - projection-free-accel.pdf. (OK)

M.L.N. Goncalves, J.G. Melo and R.D.C. Monteiro: “Projection-free accelerated method for convex optimization”, published online on*Optimization Methods and Software (2020) 1-27*(https://doi.org/10.1080/10556788.2020.1734806). - sp_AIPP.pdf.

W. Kong and R.D.C. Monteiro, ”An accelerated inexact proximal point method for solving nonconvex-concave min-max problems”,*SIAM Journal on Optimization*31 (2021) 2558-2585 (__https://doi.org/10.1137/20M1313222).__ - avg.curv.pdf. (OK)

J. Liang and R.D.C. Monteiro, ”An average curvature accelerated composite gradient method for nonconvex smooth composite optimization problems”,*SIAM Journal on Optimization*31 (2021) 217-243 (DOI: 10.1137/19M1294277). - decomp_algo.pdf. (OK)

V. Guigues and R.D.C. Monteiro, ”Stochastic Dynamic Cutting Plane for multistage stochastic convex programs”,*Journal of Optimization Theory and Applications*189 (2021) 513-559 (https://doi.org/10.1007/s10957-021-01842-x) - decomp_algo_inexact_cuts.pdf. (OK)

V. Guigues, R.D.C. Monteiro and B.F. Svaiter, ”Inexact cuts in stochastic dual dynamic programming applied to multistage stochastic nondifferentiable problems”, SIAM Journal on Optimization 31-3 (2021) 2084-2110 (https://doi.org/10.1137/20M1330075). - prox-bundle-variant.pdf. (OK)

J. Liang and R.D.C. Monteiro, ”A proximal bundle variant with optimal iteration-complexity for a large range of prox stepsizes”, SIAM Journal on Optimization 31-4 (2021) 2955-2986. - IPAAL-SIAM.pdf.

J.G. Melo, R.D.C. Monteiro and H. Wang, ”Iteration-complexity of an inexact proximal accelerated augmented Lagrangian method for solving linearly constrained smooth nonconvex composite optimization problems”, working paper, April 2020 (submitted to SIOPT). - IPAAL-JOTA.pdf.

J.G. Melo, R.D.C. Monteiro and H. Wang, ”A Proximal Augmented Lagrangian Method for Linearly

Constrained Nonconvex Composite Optimization Problems”, published online in Journal of Optimization Theory and Applications (2023) (https://doi.org/10.1007/s10957-023-02218-z) - spectral-icg.pdf. (OK)

W. Kong and R.D.C. Monteiro, ”Accelerated Inexact Composite Gradient Methods for Nonconvex Spectral Optimization Problems”, Computational Optimization and Applications 82 (2022) 673-715. - lin-ippal.pdf. (OK)

W. Kong, J.G. Melo, and R.D.C. Monteiro, ”Iteration-complexity of an inner accelerated inexact proximal augmented Lagrangian method based on the classical Lagrangian function”, SIAM Journal on Optimization 33-1 (2023) 181-210 - nlp-ippal-final.pdf. (OK)

W. Kong, J.G. Melo, and R.D.C. Monteiro, ”Iteration-complexity of a proximal augmented Lagrangian method for solving nonconvex composite optimization problems with nonlinear convex constraints”, Mathematics of Operations Research 48 (2) (2023) 1066-1094 - ac-fista.pdf. (OK)

J. Liang and R.D.C. Monteiro, ”Average curvature FISTA for nonconvex smooth composite optimization problems”, Computational Optimization and Applications 86 (2023) 275-302 (DOI 10.1007/s10589-023-00490-3) - bundle-smooth-version2.pdf.

J. Liang and R.D.C. Monteiro, ”A unified analysis of a class of proximal bundle methods for solving hybrid convex composite optimization problems”, Mathematics of Operations Research, published online on Dec 2023. - dampened-ALM-ver3.pdf. (OK)

W. Kong and R.D.C. Monteiro, ”An Accelerated Inexact Dampened Augmented Lagrangian Method for Linearly-Constrained Nonconvex Composite Optimization Problems”, Computational Optimization and Applications, 95-2 (2023) 509-545 (DOI 10.1007/s10589-023-00464-5). - global-ADMM-ver3.pdf. (OK)

W. Kong and R.D.C. Monteiro, ”Global complexity bound of a proximal ADMM for linearly-constrained nonseparable nonconvex composite programming”, SIAM Journal on Optimization, 34-1 (2024) 201-224 - stoc-one-cut-bundle-ver2.pdf.

J. Liang, V. Guigues, and R.D.C. Monteiro, ”A single cut proximal bundle method for stochastic convex composite optimization”, Mathematical Programming , published online on Dec 2023 (10.1007/s10107-023-02035-2) 1-36. - AS_PAL-ver2.pdf.

A. Sujanani and R.D.C. Monteiro, ”An adaptive superfast inexact proximal augmented Lagrangian method for smooth nonconvex composite optimization problems”, J. of Scientific Computing 97-2 (2023) 34. - Bundle_weakly_convex.pdf.

J. Liang, R.D.C. Monteiro, and H. Zhang, ”Proximal bundle methods for hybrid weakly convex composite optimization problems”, working paper, March 26th, 2023. - hallar.pdf.

R.D.C. Monteiro, A. Sujanani, and D. Cifuentes, “A low-rank augmented Lagrangian method for large-scale semidefinite programming based on a hybrid convex-nonconvex approach”, working paper, January 22, 2024 (submitted to Mathematical Programming). - universal-methods.pdf.

V. Guigues, J. Liang, and R.D.C. Monteiro, “Universal subgradient and proximal bundle methods for convex and strongly convex hybrid composite optimization”, working paper, July 14, 2024 (submitted to SIAM J. on Opt) arXiv preprint arXiv:2407.10073 - adaptive-ADMM.pdf.

L.F. Maia, D.H. Gutman, R.D.C. Monteiro, G.N. Silva, “An Adaptive Proximal ADMM for Nonconvex Linearly-Constrained Composite Programs”, working paper, July 12, 2024 (submitted to SIAM J. on Opt) arXiv preprint arXiv:2407.09927