Results 71 to 80 of about 9,205,712 (248)
Vector Optimization of Neural Network Classifiers
, 2017 In Chapter 10, the problem content and statement of the problem of vector optimization of neural network classifiers is given. Method of solution is proposed. Vector optimization of a neural network texts classifier method is proposed.
core +1 more source
Advances in Bio‐Integrated Edge Computing Systems for Smart and Connected Health
Advanced Materials, EarlyView.This review explores advances in bio‐integrated edge computing for healthcare, focusing on co‐designing computing, sensing, and energy strategies to overcome integration and power challenges for optimized, decentralized operation. ABSTRACT Recent advances in bio‐integrated healthcare technologies have enabled continuous, high‐resolution monitoring and ...
Gyuwon Kim +4 more
wiley +1 more source
Mathematics, 2020 This article has two objectives. Firstly, we use the vector variational-like inequalities problems to achieve local approximate (weakly) efficient solutions of the vector optimization problem within the novel field of the Hadamard manifolds.
Gabriel Ruiz-Garzón +3 more
doaj +1 more source
First-Order Conditions for C0,1 Constrained vector optimization [PDF]
For a Fritz John type vector optimization problem with C0,1 data we define different type of solutions, give their scalar characterizations applying the so called oriented distance, and give necessary and sufficient first order optimality conditions in ...
Rocca Matteo +2 more
core
Advanced Materials Technologies, EarlyView.High‐aspect‐ratio low‐melting‐point alloy inclusions are embedded within multilayer silicone laminates to create thermally programmable stiffness. Sequential activation of alloy‐rich layers produces four distinct mechanical states and reconfigures tendon‐driven actuator trajectories under the same load.
Palpolage Don Shehan Hiroshan Gunawardane +4 more
wiley +1 more source
An Optimized Method for Semi-supervised Support Vector Machines
Gong-kuang zidonghua, 2010 In view of problem of non-convex optimization problem that semi-supervised support vector machines use margin maximization principle to classify labeled and unlabeled samples, a method EDA_S3VM was proposed which using estimation of distribution ...
WANG Yong +3 more
doaj
A Discrete-time Neural Network for Solving Convex Optimization Problem in Support Vector Machine
Journal of Harbin University of Science and Technology, 2018 This paper proposes a discrete-time neural network model to solve the convex optimization problem deduced by a positive-kernel-based support vector machine ( SVM) .
LIU Feng-qiu, ZHANG Hong-xu
doaj +1 more source
Box-constrained vector optimization: a steepest descent method without “a priori” scalarization [PDF]
In this paper a notion of descent direction for a vector function defined on a box is introduced. This concept is based on an appropriate convex combination of the “projected” gradients of the components of the objective functions.
Miglierina Enrico +2 more
core
Advanced Materials Technologies, EarlyView.Dense tactile streams from across the humanoid body converge on collide in a central wiring and data bottleneck. By relocating computation closer to and then into the skin itself, near‐ and in‐sensor architectures, together with neuromorphic computing, chart a path toward perception‐native electronic skin, in which the conversion of stimulus into ...
Mijin Kim +6 more
wiley +1 more source
Reconstruction of Complex Discrete-Valued Vector via Convex Optimization With Sparse Regularizers
IEEE Access, 2018 In this paper, we propose a method for the reconstruction of a complex discrete-valued vector from its linear measurements. In particular, we mainly focus on the underdetermined cases, where the number of measurements is less than that of the unknown ...
Ryo Hayakawa, Kazunori Hayashi
doaj +1 more source