-
Simulated Annealing Dedicated to Maximin Latin Hypercube Designs
The dataset used to test the proposed new mutation and evaluation function. -
Maximin Latin Hypercube Designs
The Maximin Latin Hypercube Designs dataset is used to test the proposed new mutation and evaluation function. -
Traveling Salesman Problem (TSP) instances
The dataset used in the paper is the Traveling Salesman Problem (TSP) instances, specifically the Burma'7 instance, and six additional instances with 5 to 14 nodes. -
Swarm Intelligence: Past, Present and Future
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used various optimization algorithms to solve complex problems. -
Benchmark Test-Suite
The benchmark test-suite is a collection of twelve well-known test functions from the literature, including unimodal, multimodal, separable, and non-separable functions. The... -
A finite algorithm for finding the projection of a point onto the canonical s...
The (cid:96)1 ball constrained optimization problem. -
ACoS Dataset
The dataset used in the paper is a collection of 30 test functions with 30 and 50 dimensions, used for evaluating the performance of the Adaptive Coordinate System (ACoS)... -
A Data-Centric Optimization Framework for Machine Learning
DaCeML is a Data-Centric Machine Learning framework that provides a simple, flexible, and customizable pipeline for optimizing training of arbitrary deep neural networks. -
Adam: A method for stochastic optimization
This dataset is used to test the robustness of watermarking methods against adaptive attacks. -
Consistance de la minimisation du risque empirique pour l’optimisation de l’e...
The dataset used in the paper is not explicitly described, but it is mentioned that it is a class of regression models GN. -
CEC2022 basic benchmark problems
The CEC2022 basic benchmark problems dataset, which includes 5 problems from the CEC2022 benchmark suite. -
Branin function
The Branin function is a well-known function for benchmarking optimization methods. It is a 2D function with three global maxima. -
Synthetic dataset for optimal geometry generation
A synthetic dataset created for the purpose of training a generative model for optimal geometry generation. -
BENCHMARK ASSESSMENT FOR DEEPSPEED OPTIMIZATION LIBRARY
Deep Learning (DL) models are widely used in machine learning due to their performance and ability to deal with large datasets while producing high accuracy and performance... -
Cost Function Library benchmark
The dataset used in this paper is the Cost Function Library benchmark. -
Rosenbrock function
The dataset used in the paper is not explicitly mentioned, but it is mentioned that the authors used Rosenbrock function for optimization.
