Results 1 to 10 of about 66,063 (262)
Derivative-free optimization adversarial attacks for graph convolutional networks [PDF]
PeerJ Computer Science, 2021 In recent years, graph convolutional networks (GCNs) have emerged rapidly due to their excellent performance in graph data processing. However, recent researches show that GCNs are vulnerable to adversarial attacks.
Runze Yang, Teng Long
doaj +3 more sources
High-dimensional normalized data profiles for testing derivative-free optimization algorithms [PDF]
PeerJ Computer Science, 2022 This article provides a new tool for examining the efficiency and robustness of derivative-free optimization algorithms based on high-dimensional normalized data profiles that test a variety of performance metrics.
Hassan Musafer +2 more
doaj +3 more sources
IEEE Access, 2023 The deployment of offshore platforms for the extraction of oil and gas from subsea reservoirs presents unique challenges, particularly when multiple platforms are connected by a subsea gas network.
Carlos Luguesi +4 more
doaj +1 more source
Hyperparameter Optimization of a Parallelized LSTM for Time Series Prediction
Vietnam Journal of Computer Science, 2023 Long Short-Term Memory (LSTM) Neural Network has great potential to predict sequential data. Time series prediction is one of the most popular experimental subjects of LSTM.
Muhammed Maruf Öztürk
doaj +1 more source
Fractal and Fractional, 2022 This paper presents a design and evaluation of a fractional-order self optimizing control (FOSOC) architecture for process control. It is based on a real-time derivative-free optimization layer that adjusts the parameters of a discrete-time fractional ...
Jairo Viola, YangQuan Chen
doaj +1 more source
Novel Algorithm for Linearly Constrained Derivative Free Global Optimization of Lipschitz Functions
Mathematics, 2023 This paper introduces an innovative extension of the DIRECT algorithm specifically designed to solve global optimization problems that involve Lipschitz continuous functions subject to linear constraints.
Linas Stripinis, Remigijus Paulavičius
doaj +1 more source
On q-Quasi-Newton’s Method for Unconstrained Multiobjective Optimization Problems
Mathematics, 2020 A parameter-free optimization technique is applied in Quasi-Newton’s method for solving unconstrained multiobjective optimization problems. The components of the Hessian matrix are constructed using q-derivative, which is positive definite at every ...
Kin Keung Lai +2 more
doaj +1 more source
Hybridization of Multi-Objective Deterministic Particle Swarm with Derivative-Free Local Searches
Mathematics, 2020 The paper presents a multi-objective derivative-free and deterministic global/local hybrid algorithm for the efficient and effective solution of simulation-based design optimization (SBDO) problems.
Riccardo Pellegrini +5 more
doaj +1 more source
Two decades of blackbox optimization applications
EURO Journal on Computational Optimization, 2021 This article reviews blackbox optimization applications of direct search optimization methods over the past twenty years. Emphasis is placed on the Mesh Adaptive Direct Search (Mads) derivative-free optimization algorithm.
Stéphane Alarie +4 more
doaj +1 more source
On the implementation of a global optimization method for mixed-variable problems
Open Journal of Mathematical Optimization, 2021 We describe the optimization algorithm implemented in the open-source derivative-free solver RBFOpt. The algorithm is based on the radial basis function method of Gutmann and the metric stochastic response surface method of Regis and Shoemaker.
Nannicini, Giacomo
doaj +1 more source