Alliance. The autonomous trait of self-optimization involves no human intervention at all during the aforementioned optimization process. In the area of control...

hyperparameter optimization methods. Bayesian optimization is a global optimization method for noisy black-box functions. Applied to hyperparameter optimization, Bayesian...

A self-organizing network (SON) is an automation technology designed to make the planning, configuration, management, optimization and healing of mobile...

operation Self-optimization Automatic monitoring and control of resources to ensure the optimal functioning with respect to the defined requirements Self-protection...

numerous optimization tasks involving some sort of graph, e.g., vehicle routing and internet routing. As an example, ant colony optimization is a class...

individuals and society, such as self-optimization (the quantified self), societal optimizations (e.g., by smart cities) and optimized services (including various...

by using another overlaying optimizer, a concept known as meta-optimization, or even fine-tuned during the optimization, e.g., by means of fuzzy logic...

In computer science, program optimization, code optimization, or software optimization is the process of modifying a software system to make some aspect...

the performance of the system. Topology optimization is different from shape optimization and sizing optimization in the sense that the design can attain...

Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets (or, equivalently...

graphs. An example of such an optimization problem is graph coloring. The SOC process apparently helps the optimization from getting stuck in a local...

properties. Self-configuration: Automatic configuration of components; Self-healing: Automatic discovery, and correction of faults; Self-optimization: Automatic...

characterized by the properties of self-organization, self-configuration, self-optimization, self-healing, self-protection, self-explaining, and context awareness...

align with the "will of the universe". Land focuses on capitalist self-optimization as the driver of modernity, progress, and the eroding of existing...

computing, computing systems with properties of self-configuration, self-optimization, self-healing, and/or self-protection Organic search, search results through...

are capable of presenting self-organized behavior is an active research area. Optimization algorithms can be considered self-organizing because they aim...

Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute...

protocol Reinforcement learning Rule 110 Self-organized criticality Spiral optimization algorithm Stochastic optimization Swarm Development Group Swarm robotic...

Proximal policy optimization (PPO) is a reinforcement learning (RL) algorithm for training an intelligent agent. Specifically, it is a policy gradient...

A self-concordant function is a function satisfying a certain differential inequality, which makes it particularly easy for optimization using Newton's...

GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, and causal inference. In...

Plume is a Software-as-a-Service (SaaS) company that provides self-optimizing WiFi services, visibility, and network control for Communications Service...

already been introduced, and was added to SGD optimization techniques in 1986. However, these optimization techniques assumed constant hyperparameters,...

{\displaystyle g_{i}(x)\geqslant 0,i=1,\ldots ,r} . Global optimization is distinguished from local optimization by its focus on finding the minimum or maximum over...

that the data structure implementing the abstract type varies in a "self-optimizing" way. Normal algebraic data type parameters can only describe data...

Gradient descent is a method for unconstrained mathematical optimization. It is a first-order iterative algorithm for minimizing a differentiable multivariate...

Particle Swarm Optimization and it is an array of values of a candidate solution of optimization problem. The cost function of the optimization problem determines...

order to optimize a set of network performance indicators. Different studies in beam tilt optimization focus on Coverage-Capacity Optimization (CCO), for...

not necessary since the database includes some kind of automatic self-optimization (like automatic indices, table statistics, and distributing of data)...

piece of hardware, where data placement optimization is performed either entirely by the device (self-optimized mode), or through placement "hints" supplied...