Results 71 to 80 of about 24,030 (229)

A New Nonsmooth Bundle-Type Approach for a Class of Functional Equations in Hilbert Spaces

open access: yesJournal of Function Spaces, 2017
A new bundle-type approach for solving a class of functional equations is presented by combining bundle idea for nonsmooth optimization with common iterative process for functional equations.
Jie Shen   +3 more
doaj   +1 more source

Incremental and Parallel Machine Learning Algorithms With Automated Learning Rate Adjustments

open access: yesFrontiers in Robotics and AI, 2019
The existing machine learning algorithms for minimizing the convex function over a closed convex set suffer from slow convergence because their learning rates must be determined before running them.
Kazuhiro Hishinuma, Hideaki Iiduka
doaj   +1 more source

Remora‐Inspired Sensing Suction Cup with Adhesion Monitoring and Force Detection

open access: yesAdvanced Intelligent Systems, Volume 8, Issue 2, February 2026.
A suction cup with integrated liquid metal microchannel sensors enables stable multidirectional force sensing and adhesion monitoring in both air and water. The flexible resistive sensors, placed on the outer lip, transduce deformations into resistance changes under normal and shear loads.
Yuchen Liu   +7 more
wiley   +1 more source

Optimization problems with quasiconvex inequality constraints [PDF]

open access: yes
The constrained optimization problem min f(x), gj(x) 0 (j = 1, . . . , p) is considered, where f : X ! R and gj : X ! R are nonsmooth functions with domain X Rn.
Ginchev Ivan, Ivanov Vsevolod
core  

Proximal Bundle Method for Contact Shape Optimization Problem

open access: yesAdvances in Electrical and Electronic Engineering, 2017
From the mathematical point of view, the contact shape optimization is a problem of nonlinear optimization with a specific structure, which can be exploited in its solution. In this paper, we show how to overcome the difficulties related to the nonsmooth
Nikola Plivova, Petr Beremlijski
doaj   +1 more source

A New Proximal Iteratively Reweighted Nuclear Norm Method for Nonconvex Nonsmooth Optimization Problems

open access: yesMathematics
This paper proposes a new proximal iteratively reweighted nuclear norm method for a class of nonconvex and nonsmooth optimization problems. The primary contribution of this work is the incorporation of line search technique based on dimensionality ...
Zhili Ge, Siyu Zhang, Xin Zhang, Yan Cui
doaj   +1 more source

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