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ORCIDSIAM Journal on Optimization, Volume 32
Volume 32, Number 1, March 2022
- Ran Xin, Usman A. Khan, Soummya Kar
:
Fast Decentralized Nonconvex Finite-Sum Optimization with Recursive Variance Reduction. 1-28 - Hao-Jun Michael Shi, Yuchen Xie, Richard H. Byrd, Jorge Nocedal:
A Noise-Tolerant Quasi-Newton Algorithm for Unconstrained Optimization. 29-55 - Jae-Hyoung Lee, Tien-Son Pham:
Openness, Hölder Metric Regularity, and Hölder Continuity Properties of Semialgebraic Set-Valued Maps. 56-74 - Christian Kirches, Jeffrey Larson, Sven Leyffer, Paul Manns:
Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints. 75-99 - Na Zhang, Qia Li:
First-Order Algorithms for a Class of Fractional Optimization Problems. 100-129 - Darinka Dentcheva, Yang Lin:
Bias Reduction in Sample-Based Optimization. 130-151 - Christian Biefel, Frauke Liers, Jan Rolfes, Martin Schmidt:
Affinely Adjustable Robust Linear Complementarity Problems. 152-172 - Antonio De Rosa, Aida Khajavirad:
The Ratio-Cut Polytope and K-Means Clustering. 173-203 - Shoham Sabach, Marc Teboulle:
Faster Lagrangian-Based Methods in Convex Optimization. 204-227 - Xiaoyu He, Zibin Zheng, Yuren Zhou, Chuan Chen:
QNG: A Quasi-Natural Gradient Method for Large-Scale Statistical Learning. 228-255 - Bram L. Gorissen:
Interior Point Methods Can Exploit Structure of Convex Piecewise Linear Functions with Application in Radiation Therapy. 256-275 - Adrian S. Lewis, Jingwei Liang, Tonghua Tian:
Partial Smoothness and Constant Rank. 276-291 - Immanuel M. Bomze, Markus Gabl:
Uncertainty Preferences in Robust Mixed-Integer Linear Optimization with Endogenous Uncertainty. 292-318 - Eduardo Casas, Mariano Mateos:
Corrigendum: Critical Cones for Sufficient Second Order Conditions in PDE Constrained Optimization. 319-320
Volume 32, Number 2, June 2022
- Khaled M. Elbassioni, Kazuhisa Makino, Waleed Najy:
Finding Sparse Solutions for Packing and Covering Semidefinite Programs. 321-353 - Ying Sun, Gesualdo Scutari, Amir Daneshmand:
Distributed Optimization Based on Gradient Tracking Revisited: Enhancing Convergence Rate via Surrogation. 354-385 - Dionysios S. Kalogerias, Warren B. Powell:
Zeroth-Order Stochastic Compositional Algorithms for Risk-Aware Learning. 386-416 - Saul Toscano-Palmerin, Peter I. Frazier:
Bayesian Optimization with Expensive Integrands. 417-444 - Alejandro I. Maass, Chris Manzie, Dragan Nesic, Jonathan H. Manton, Iman Shames:
Tracking and Regret Bounds for Online Zeroth-Order Euclidean and Riemannian Optimization. 445-469 - Grigoriy Blekherman, Santanu S. Dey, Kevin Shu, Shengding Sun:
Hyperbolic Relaxation of $k$-Locally Positive Semidefinite Matrices. 470-490 - Monique Laurent, Luis Felipe Vargas:
Finite Convergence of Sum-of-Squares Hierarchies for the Stability Number of a Graph. 491-518 - Krishnakumar Balasubramanian, Saeed Ghadimi, Anthony Nguyen:
Stochastic Multilevel Composition Optimization Algorithms with Level-Independent Convergence Rates. 519-544 - Frank E. Curtis, Yutong Dai, Daniel P. Robinson:
A Subspace Acceleration Method for Minimization Involving a Group Sparsity-Inducing Regularizer. 545-572 - Jinlong Lei, Uday V. Shanbhag:
Distributed Variable Sample-Size Gradient-Response and Best-Response Schemes for Stochastic Nash Equilibrium Problems. 573-603 - Rongzhu Ke, Wei Yao, Jane J. Ye, Jin Zhang:
Generic Property of the Partial Calmness Condition for Bilevel Programming Problems. 604-634 - Alberto Seeger:
Condition Number Minimization in Euclidean Jordan Algebras. 635-658 - Santanu S. Dey, Gonzalo Muñoz, Felipe Serrano:
On Obtaining the Convex Hull of Quadratic Inequalities via Aggregations. 659-686 - HanQin Cai, Daniel McKenzie, Wotao Yin, Zhenliang Zhang:
Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling. 687-714 - Yu Mei, Jia Liu, Zhiping Chen:
Distributionally Robust Second-Order Stochastic Dominance Constrained Optimization with Wasserstein Ball. 715-738 - Andrea Cristofari:
Active-Set Identification with Complexity Guarantees of an Almost Cyclic 2-Coordinate Descent Method with Armijo Line Search. 739-764 - Philippe Moustrou, Helen Naumann, Cordian Riener, Thorsten Theobald, Hugues Verdure:
Symmetry Reduction in AM/GM-Based Optimization. 765-785 - Guillaume Carlier:
On the Linear Convergence of the Multimarginal Sinkhorn Algorithm. 786-794 - Nurdan Kuru, S. Ilker Birbil, Mert Gürbüzbalaban, Sinan Yildirim:
Differentially Private Accelerated Optimization Algorithms. 795-821 - Mitsuaki Obara, Takayuki Okuno, Akiko Takeda:
Sequential Quadratic Optimization for Nonlinear Optimization Problems on Riemannian Manifolds. 822-853 - Maurício Silva Louzeiro, Ronny Bergmann, Roland Herzog:
Fenchel Duality and a Separation Theorem on Hadamard Manifolds. 854-873 - Terunari Fuji, Pierre-Louis Poirion, Akiko Takeda:
Convexification with Bounded Gap for Randomly Projected Quadratic Optimization. 874-899 - Aleksandr Y. Aravkin, Robert J. Baraldi, Dominique Orban:
A Proximal Quasi-Newton Trust-Region Method for Nonsmooth Regularized Optimization. 900-929 - Shanyin Tong, Anirudh Subramanyam, Vishwas Rao:
Optimization under Rare Chance Constraints. 930-958 - Ting Tao, Yitian Qian, Shaohua Pan:
Column $\ell_{2, 0}$-Norm Regularized Factorization Model of Low-Rank Matrix Recovery and Its Computation. 959-988 - Sivaramakrishnan Ramani, Archis Ghate:
Robust Markov Decision Processes with Data-Driven, Distance-Based Ambiguity Sets. 989-1017 - Shuyang Ling:
Improved Performance Guarantees for Orthogonal Group Synchronization via Generalized Power Method. 1018-1048 - Jerzy Grzybowski, Ryszard Urbanski:
Minimal Pairs of Convex Sets Which Share a Recession Cone. 1049-1068 - Axel Séguin, Daniel Kressner:
Continuation Methods for Riemannian Optimization. 1069-1093 - Adrian S. Lewis, Genaro López-Acedo, Adriana Nicolae:
Local Linear Convergence of Alternating Projections in Metric Spaces with Bounded Curvature. 1094-1119 - Georgios Kotsalis, Guanghui Lan, Tianjiao Li:
Simple and Optimal Methods for Stochastic Variational Inequalities, II: Markovian Noise and Policy Evaluation in Reinforcement Learning. 1120-1155 - Sungho Shin, Mihai Anitescu, Victor M. Zavala:
Exponential Decay of Sensitivity in Graph-Structured Nonlinear Programs. 1156-1183 - Gabriele Eichfelder, Ernest Quintana, Stefan Rocktäschel:
A Vectorization Scheme for Nonconvex Set Optimization Problems. 1184-1209 - Eduard Gorbunov, Pavel E. Dvurechensky, Alexander V. Gasnikov:
An Accelerated Method for Derivative-Free Smooth Stochastic Convex Optimization. 1210-1238 - Abraham P. Vinod, Arie Israel, Ufuk Topcu:
Constrained, Global Optimization of Unknown Functions with Lipschitz Continuous Gradients. 1239-1264 - Martin Brokate, Michael Ulbrich:
Newton Differentiability of Convex Functions in Normed Spaces and of a Class of Operators. 1265-1287 - Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher:
On the Convergence of Stochastic Primal-Dual Hybrid Gradient. 1288-1318 - Santanu S. Dey, Aleksandr M. Kazachkov, Andrea Lodi, Gonzalo Muñoz:
Cutting Plane Generation through Sparse Principal Component Analysis. 1319-1343 - Lennart Sinjorgo, Renata Sotirov:
On the Generalized $\vartheta$-Number and Related Problems for Highly Symmetric Graphs. 1344-1378 - Xianfu Wang, Heinz H. Bauschke:
The Bregman Proximal Average. 1379-1401 - Youhei Akimoto, Anne Auger, Tobias Glasmachers, Daiki Morinaga:
Global Linear Convergence of Evolution Strategies on More than Smooth Strongly Convex Functions. 1402-1429 - Jean B. Lasserre:
Optimization on the Euclidean Unit Sphere. 1430-1445 - William B. Haskell, Huifu Xu, Wenjie Huang:
Preference Robust Optimization for Choice Functions on the Space of CDFs. 1446-1470 - Henry Lam, Fengpei Li:
General Feasibility Bounds for Sample Average Approximation via Vapnik-Chervonenkis Dimension. 1471-1497
Volume 32, Number 3, September 2022
- Daniel Duque, Sanjay Mehrotra, David P. Morton:
Distributionally Robust Two-Stage Stochastic Programming. 1499-1522 - Lei Yang, Kim-Chuan Toh:
Bregman Proximal Point Algorithm Revisited: A New Inexact Version and Its Inertial Variant. 1523-1554 - Rui Yuan, Alessandro Lazaric, Robert M. Gower:
Sketched Newton-Raphson. 1555-1583 - Xiaokai Chang, Junfeng Yang, Hongchao Zhang:
Golden Ratio Primal-Dual Algorithm with Linesearch. 1584-1613 - Wenjing Li, Wei Bian, Kim-Chuan Toh:
Difference-of-Convex Algorithms for a Class of Sparse Group $\ell_0$ Regularized Optimization Problems. 1614-1641 - Monika Eisenmann, Tony Stillfjord:
Sublinear Convergence of a Tamed Stochastic Gradient Descent Method in Hilbert Space. 1642-1667 - Jelena Diakonikolas, Puqian Wang:
Potential Function-Based Framework for Minimizing Gradients in Convex and Min-Max Optimization. 1668-1697 - Hamed Rahimian, Güzin Bayraksan, Tito Homem-de-Mello:
Effective Scenarios in Multistage Distributionally Robust Optimization with a Focus on Total Variation Distance. 1698-1727 - Dawei Li, Tian Ding, Ruoyu Sun:
On the Benefit of Width for Neural Networks: Disappearance of Basins. 1728-1758 - Jason M. Altschuler, Pablo A. Parrilo:
Approximating Min-Mean-Cycle for Low-Diameter Graphs in Near-Optimal Time and Memory. 1791-1816 - Jean-François Aujol, Charles Dossal, Aude Rondepierre:
Convergence Rates of the Heavy Ball Method for Quasi-strongly Convex Optimization. 1817-1842 - Charles Audet, Alain Batailly, Solène Kojtych:
Escaping Unknown Discontinuous Regions in Blackbox Optimization. 1843-1870 - Thomas Bittar, Pierre Carpentier, Jean-Philippe Chancelier, Jérôme Lonchampt:
The Stochastic Auxiliary Problem Principle in Banach Spaces: Measurability and Convergence. 1871-1900 - Harsha Gangammanavar, Manish Bansal:
Stochastic Decomposition Method for Two-Stage Distributionally Robust Linear Optimization. 1901-1930 - Wei Liu, Xin Liu, Xiaojun Chen:
Linearly Constrained Nonsmooth Optimization for Training Autoencoders. 1931-1957 - Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy:
Escaping Strict Saddle Points of the Moreau Envelope in Nonsmooth Optimization. 1958-1983 - Massimo Fornasier, Hui Huang, Lorenzo Pareschi, Philippe Sünnen:
Anisotropic Diffusion in Consensus-Based Optimization on the Sphere. 1984-2012 - Abdessamad Barbara, Abderrahim Jourani:
Error Bound Characterizations of the Conical Constraint Qualification in Convex Programming. 2013-2040 - Georgios Kotsalis, Guanghui Lan, Tianjiao Li:
Simple and Optimal Methods for Stochastic Variational Inequalities, I: Operator Extrapolation. 2041-2073 - Hédy Attouch, Jalal Fadili:
From the Ravine Method to the Nesterov Method and Vice Versa: A Dynamical System Perspective. 2074-2101 - Sergiy Butenko, Mykyta Makovenko, Panos M. Pardalos:
A Hierarchy of Standard Polynomial Programming Formulations for the Maximum Clique Problem. 2102-2128 - Lin Chen, Yongchao Liu, Xinmin Yang, Jin Zhang:
Stochastic Approximation Methods for the Two-Stage Stochastic Linear Complementarity Problem. 2129-2155 - Jesús A. De Loera, Sean Kafer, Laura Sanità:
Pivot Rules for Circuit-Augmentation Algorithms in Linear Optimization. 2156-2179 - Joong-Ho Won, Teng Zhang, Hua Zhou:
Orthogonal Trace-Sum Maximization: Tightness of the Semidefinite Relaxation and Guarantee of Locally Optimal Solutions. 2180-2207 - Brian Bullins, Kevin A. Lai:
Higher-Order Methods for Convex-Concave Min-Max Optimization and Monotone Variational Inequalities. 2208-2229 - Puya Latafat, Andreas Themelis, Masoud Ahookhosh, Panagiotis Patrinos:
Bregman Finito/MISO for Nonconvex Regularized Finite Sum Minimization without Lipschitz Gradient Continuity. 2230-2262 - Hoai An Le Thi, Ngai Van Huynh, Tao Pham Dinh, Hoang Phuc Hau Luu:
Stochastic Difference-of-Convex-Functions Algorithms for Nonconvex Programming. 2263-2293 - Yancheng Yuan, Tsung-Hui Chang, Defeng Sun, Kim-Chuan Toh:
A Dimension Reduction Technique for Large-Scale Structured Sparse Optimization Problems with Application to Convex Clustering. 2294-2318 - Jiawei Zhang, Zhi-Quan Luo:
A Global Dual Error Bound and Its Application to the Analysis of Linearly Constrained Nonconvex Optimization. 2319-2346 - Bruno F. Lourenço, Vera Roshchina, James Saunderson:
Amenable Cones Are Particularly Nice. 2347-2375 - Kristian Bredies, Enis Chenchene, Dirk A. Lorenz, Emanuele Naldi:
Degenerate Preconditioned Proximal Point Algorithms. 2376-2401 - Nikita Doikov, Yurii E. Nesterov:
High-Order Optimization Methods for Fully Composite Problems. 2402-2427 - Simone Rebegoldi, Luca Calatroni:
Scaled, Inexact, and Adaptive Generalized FISTA for Strongly Convex Optimization. 2428-2459
Volume 32, Number 4, December 2022
- Maria M. Davis, Dávid Papp:
Dual Certificates and Efficient Rational Sum-of-Squares Decompositions for Polynomial Optimization over Compact Sets. 2461-2492 - Martina Cerulli, Antoine Oustry, Claudia D'Ambrosio, Leo Liberti:
Convergent Algorithms for a Class of Convex Semi-infinite Programs. 2493-2526 - David Wu, David R. Palmer, Daryl R. DeFord:
Maximum A Posteriori Inference of Random Dot Product Graphs via Conic Programming. 2527-2551 - Matthew Hough, Lindon Roberts:
Model-Based Derivative-Free Methods for Convex-Constrained Optimization. 2552-2579 - Yuzixuan Zhu, Deyi Liu, Quoc Tran-Dinh:
New Primal-Dual Algorithms for a Class of Nonsmooth and Nonlinear Convex-Concave Minimax Problems. 2580-2611 - Lucas Slot:
Sum-of-Squares Hierarchies for Polynomial Optimization and the Christoffel-Darboux Kernel. 2612-2635 - Yang Liu, Fred Roosta:
MINRES: From Negative Curvature Detection to Monotonicity Properties. 2636-2661 - Qiong Wu, Huifu Xu:
Preference Robust Modified Optimized Certainty Equivalent. 2662-2689 - Hiroyuki Sato:
Riemannian Conjugate Gradient Methods: General Framework and Specific Algorithms with Convergence Analyses. 2690-2717 - S. Rasoul Etesami:
Maximizing Convergence Time in Network Averaging Dynamics Subject to Edge Removal. 2718-2744 - Kevin Huang, Shuzhong Zhang:
New First-Order Algorithms for Stochastic Variational Inequalities. 2745-2772 - Fabián Flores Bazán, A. Hantoute:
Convex Representatives of the Value Function and Aumann Integrals in Normed Spaces. 2773-2796 - Shiyu Liang, Ruoyu Sun, R. Srikant:
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity. 2797-2827 - Divya Padmanabhan, Selin Damla Ahipasaoglu, Arjun Kodagehalli Ramachandra, Karthik Natarajan:
Extremal Probability Bounds in Combinatorial Optimization. 2828-2858 - Jesús Camacho Moro, María J. Cánovas, Juan Parra:
From Calmness to Hoffman Constants for Linear Semi-infinite Inequality Systems. 2859-2878 - Mingyi Hong, Siliang Zeng, Junyu Zhang, Haoran Sun:
On the Divergence of Decentralized Nonconvex Optimization. 2879-2908 - Xiaojun Chen, Jinglai Shen:
Dynamic Stochastic Variational Inequalities and Convergence of Discrete Approximation. 2909-2937 - Haoyue Wang, Haihao Lu, Rahul Mazumder:
Frank-Wolfe Methods with an Unbounded Feasible Region and Applications to Structured Learning. 2938-2968 - Marcus Carlsson, Daniele Gerosa, Carl Olsson:
An Unbiased Approach to Low Rank Recovery. 2969-2996
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