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 (to be submitted).