1.
Proximal alternating linearized minimization for nonconvex and nonsmooth problems
by Bolte, Jérôme
Mathematical programming, 2013, Vol.146 (1-2), p.459-494
2.
Fixed point and Bregman iterative methods for matrix rank minimization
by Ma, Shiqian
Mathematical programming, 2009, Vol.128 (1-2), p.321-353
3.
Iterative reweighted minimization methods for lp regularized unconstrained nonlinear programming
by Lu, Zhaosong
Mathematical programming, 2013, Vol.147 (1-2), p.277-307
4.
Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized Gauss–Seidel methods
by Attouch, Hedy
Mathematical programming, 2011, Vol.137 (1-2), p.91-129
5.
Optimized first-order methods for smooth convex minimization
by Kim, Donghwan
Mathematical programming, 2015, Vol.159 (1-2), p.81-107
6.
Performance of first-order methods for smooth convex minimization: a novel approach
by Drori, Yoel
Mathematical programming, 2013, Vol.145 (1-2), p.451-482
7.
A review on instance ranking problems in statistical learning
by Werner, Tino
Machine learning, 2021, Vol.111 (2), p.415-463
8.
Smoothing methods for nonsmooth, nonconvex minimization
by Chen, Xiaojun
Mathematical programming, 2012, Vol.134 (1), p.71-99
9.
An implementable proximal point algorithmic framework for nuclear norm minimization
by Liu, Yong-Jin
Mathematical programming, 2011, Vol.133 (1-2), p.399-436
10.
Accelerated topology optimization design of 3D structures based on deep learning
by Xiang, Cheng
Structural and multidisciplinary optimization, 2022, Vol.65 (3)
11.
On label dependence and loss minimization in multi-label classification
by Dembczyński, Krzysztof
Machine learning, 2012, Vol.88 (1-2), p.5-45
12.
A framework of constraint preserving update schemes for optimization on Stiefel manifold
by Jiang, Bo
Mathematical programming, 2014, Vol.153 (2), p.535-575
13.
A Critical Review of the Harm-Minimisation Tools Available for Electronic Gambling
by Harris, Andrew
Journal of gambling studies, 2016, Vol.33 (1), p.187-221
14.
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
by Vese, L A
International journal of computer vision, 2002, Vol.50 (3), p.271-293
15.
A Stochastic Successive Minimization Method for Nonsmooth Nonconvex Optimization with Applications to Transceiver Design in Wireless Communication Networks
by Razaviyayn, Meisam
Mathematical programming, 2016, Vol.157 (2), p.515-545
16.
The direct extension of ADMM for multi-block convex minimization problems is not necessarily convergent
by Chen, Caihua
Mathematical programming, 2014, Vol.155 (1-2), p.57-79
17.
From error bounds to the complexity of first-order descent methods for convex functions
by Bolte, Jérôme
Mathematical programming, 2016, Vol.165 (2), p.471-507
18.
Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
by Richtarik, Peter
Mathematical programming, 2012, Vol.144 (1-2), p.1-38
19.
Logarithmic regret algorithms for online convex optimization
by HAZAN, Elad
Machine learning, 2007, Vol.69 (2-3), p.169-192
20.
Universal gradient methods for convex optimization problems
by Nesterov, Yu
Mathematical programming, 2014, Vol.152 (1-2), p.381-404
