← Back to all news
arXiv Machine Learning October 2, 2026 By Weifeng Yang

Generalized Geometry Block Proximal Linearized Method for Multiblock Nonconvex and Nonsmooth Optimization

Read the original on arXiv Machine Learning →

The Flow has not summarised this story yet — read it at arXiv Machine Learning.

  • benchmarks

One email a morning, machine-written

One email a day, machine-written, one click to leave. We never share your address.

Related stories

arXiv Machine Learning
Aug 7

An Inertial Block Proximal Linearized Method with Adaptive Momentum for Nonconvex and Nonsmooth Optimization

arXiv:2608. 05502v1 Announce Type: cross Abstract: In this paper, we consider a class of multiblock nonconvex nonsmooth optimization problems, which covers many applications such as the analysis of pre-earthquake anomalies and machine learning.

By Weifeng Yang
benchmarks
More like this →
arXiv Machine Learning
Aug 14

A Local-Linearly Convergent Algorithm for Nonconvex Equality-Constrained Optimization

arXiv:2608. 12665v1 Announce Type: cross Abstract: For solving nonconvex equality-constrained optimization problems, a recent Gradient-Eigenstep Algorithm by Goyens et al.

By Frank E. Curtis, Lingjun Guo, Daniel P. Robinson
More like this →
arXiv Machine Learning
Jul 13

Nonconvex Composite Functional Constraints via First-Order Augmented Lagrangian Methods under Local Regularity

arXiv:2607. 08954v1 Announce Type: cross Abstract: We study nonasymptotic convergence of primal-dual methods for a class of nonconvex constrained optimization problems with a convex-composite structure.

By Linglingzhi Zhu, Jiajin Li
safety
More like this →
arXiv Machine Learning
Jul 9

Restricted Dynamic Geometric Complexity: Certificates for Structured Preconditioning

arXiv:2607. 07204v1 Announce Type: cross Abstract: Optimization geometrodynamics views optimizer state as evolving geometry.

By Zavier Li
benchmarks
More like this →
arXiv Statistics ML
Sep 16

A proximal augmented Lagrangian method for nonconvex optimization with equality and inequality constraints

arXiv:2509.02894v2 Announce Type: replace-cross Abstract: We propose an inexact proximal augmented Lagrangian method (P-ALM) for nonconvex structured optimization problems. The proposed method featur...

By Adeyemi D. Adeoye, Puya Latafat, Alberto Bemporad
More like this →
arXiv Machine Learning
Aug 13

Adaptive Bregman Proximal Stochastic Gradient with a Stabilized Barzilai--Borwein Step Size

arXiv:2608. 12009v1 Announce Type: cross Abstract: Bregman proximal stochastic gradient (BPSG) methods bring variance-reduced composite optimization to objectives whose geometry is poorly captured by Euclidean smoothness.

By Chenhan Jin, Shengze Xu, Binghui Xie, Kaiwen Zhou, Fan Jia, James Cheng, Tieyong Zeng
More like this →
About Pricing API Newsletter Sources Privacy Terms Refunds Accessibility Provider info Contact RSS

The Flow links to publishers and never republishes their articles. Summaries are machine-generated.

v1.1.0 · 5f852ea