We needed to create something that was fun and engaging for learners, but also useful for educators who might use it to teach optimization concepts. Our core intention was to provide a reliable and ...

Quantum annealing is a specific type of quantum computing that can use quantum physics principles to find high-quality solutions to difficult optimization problems. Rather than requiring exact ...

In order to obtain more stable solutions, a distributed approximate gradient descent optimization algorithm and conflict resolution mechanism are proposed, which enhances the convergence of our method ...

Abstract: We propose two new algorithms for solving quadratically constrained quadratic programming (QCQP) problems arising from real-time optimization based control such as model predictive control ...

Motivated by the smoothing approaches, we modify the classical bi-level gradient sequential averaging method to solve the bi-level optimization problem. Under some mild conditions, we obtain the ...

Adaptive gradient optimization methods, such as Adam ... However, these methods often suffer from suboptimal generalization compared to stochastic gradient descent (SGD) and exhibit instability, ...

This notebook illustrates the nature of the Stochastic Gradient Descent (SGD) and walks through all the necessary steps to create SGD from scratch in Python. Gradient Descent is an essential part of ...