learning, hyperparameter optimization or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a...
24 KB (2,490 words) - 06:28, 23 September 2024
instead apply concepts from derivative-free optimization or black box optimization. Apart from tuning hyperparameters, machine learning involves storing and...
10 KB (1,139 words) - 17:09, 30 September 2024
Bayesian optimization is a sequential design strategy for global optimization of black-box functions, that does not assume any functional forms. It is...
16 KB (1,686 words) - 11:58, 23 September 2024
(without constructing and training it). NAS is closely related to hyperparameter optimization and meta-learning and is a subfield of automated machine learning...
26 KB (2,980 words) - 21:57, 19 August 2024
hand-designed models. Common techniques used in AutoML include hyperparameter optimization, meta-learning and neural architecture search. In a typical machine...
9 KB (1,024 words) - 02:45, 24 July 2024
Learning rate (category Optimization algorithms and methods)
into deep learning libraries such as Keras. Hyperparameter (machine learning) Hyperparameter optimization Stochastic gradient descent Variable metric...
9 KB (1,108 words) - 10:15, 30 April 2024
forgetting Continual learning Domain adaptation Foundation model Hyperparameter optimization Overfitting Quinn, Joanne (2020). Dive into deep learning: tools...
13 KB (1,370 words) - 16:00, 16 September 2024
Proximal policy optimization (PPO) is an algorithm in the field of reinforcement learning that trains a computer agent's decision function to accomplish...
15 KB (2,048 words) - 04:23, 7 October 2024
Genetic algorithm (redirect from Optimization using genetic algorithms)
GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, and causal inference. In...
68 KB (8,038 words) - 11:58, 29 September 2024
preserved. CUR matrix approximation Data transformation (statistics) Hyperparameter optimization Information gain in decision trees Johnson–Lindenstrauss lemma...
21 KB (2,248 words) - 01:18, 10 September 2024