[BOG][B] Variational analysis and applications

BS Mordukhovich - 2018 - Springer
Boris S. Mordukhovich Page 1 Springer Monographs in Mathematics Boris S. Mordukhovich
Variational Analysis and Applications Page 2 Springer Monographs in Mathematics Editors-in-Chief …

C-mil: Continuation multiple instance learning for weakly supervised object detection

F Wan, C Liu, W Ke, X Ji, J Jiao… - Proceedings of the IEEE …, 2019 - openaccess.thecvf.com
Weakly supervised object detection (WSOD) is a challenging task when provided with image
category supervision but required to simultaneously learn object locations and object …

A globally convergent algorithm for nonconvex optimization based on block coordinate update

Y Xu, W Yin - Journal of Scientific Computing, 2017 - Springer
Nonconvex optimization arises in many areas of computational science and engineering.
However, most nonconvex optimization algorithms are only known to have local …

Support points

S Mak, VR Joseph - The Annals of Statistics, 2018 - JSTOR
This paper introduces a new way to compact a continuous probability distribution F into a set
of representative points called support points. These points are obtained by minimizing the …

Deterministic nonsmooth nonconvex optimization

M Jordan, G Kornowski, T Lin… - The Thirty Sixth …, 2023 - proceedings.mlr.press
We study the complexity of optimizing nonsmooth nonconvex Lipschitz functions by
producing $(\delta,\epsilon) $-Goldstein stationary points. Several recent works have …

A smoothing proximal gradient algorithm for nonsmooth convex regression with cardinality penalty

W Bian, X Chen - SIAM Journal on Numerical Analysis, 2020 - SIAM
In this paper, we focus on the constrained sparse regression problem, where the loss
function is convex but nonsmooth and the penalty term is defined by the cardinality function …

[BOG][B] An optimization primer

JO Royset, RJB Wets - 2022 - Springer
The concerns with finding minima and maxima were for a long time mainly restricted to
mathematical expressions stemming from physical phenomena. The preeminence of being …

MADMM: a generic algorithm for non-smooth optimization on manifolds

A Kovnatsky, K Glashoff, MM Bronstein - … 11-14, 2016, Proceedings, Part V …, 2016 - Springer
Numerous problems in computer vision, pattern recognition, and machine learning are
formulated as optimization with manifold constraints. In this paper, we propose the Manifold …

Group sparse optimization via lp, q regularization

Y Hu, C Li, K Meng, J Qin, X Yang - Journal of Machine Learning Research, 2017 - jmlr.org
In this paper, we investigate a group sparse optimization problem via lp, q regularization in
three aspects: theory, algorithm and application. In the theoretical aspect, by introducing a …

Risk-adaptive approaches to stochastic optimization: A survey

JO Royset - SIAM Review, 2025 - SIAM
Uncertainty is prevalent in engineering design and data-driven problems and, more broadly,
in decision making. Due to inherent risk-averseness and ambiguity about assumptions, it is …