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Glossario IA

Il dizionario completo dell'Intelligenza Artificiale

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Successive Halving

Progressive elimination method that halves the number of configurations at each iteration by allocating more resources to the identified best performances.

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Dynamic resource allocation

Adaptive strategy that distributes computational budget based on observed performances of hyperparameter configurations during optimization.

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Computational budget

Total available computational resource defined in terms of iterations, training epochs, or processor time allocated to hyperparameter optimization.

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Early elimination

Mechanism that prematurely stops the evaluation of underperforming configurations to save computational resources.

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ASHA

Asynchronous Successive Halving Algorithm implements Successive Halving asynchronously to maximize resource utilization on parallel architectures.

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Multi-fidelity optimization

Approach using lower-quality but faster approximations to quickly evaluate configurations before their full evaluation.

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Hyperparameter configuration

Specific set of values assigned to the hyperparameters of a machine learning model defining a unique configuration to evaluate.

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Bracket elimination

Staggered elimination process in Hyperband where multiple brackets with different initial resource allocations run in parallel.

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Resource allocation strategy

Policy determining the distribution of computational budget among hyperparameter configurations during the optimization process.

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Hyperparameter space exploration

Systematic process of searching in the hyperparameter space to identify optimal configurations according to defined performance metrics.

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Performance-based pruning

Pruning technique for configurations based on their relative performance compared to a threshold or the best observed configurations.

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Computational efficiency

Measure of how efficiently the optimization algorithm uses available resources to find performant configurations.

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Configuration fidelity

Level of precision or quality used to evaluate a hyperparameter configuration, progressively increased for the best configurations.

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Adaptive resource allocation

Mechanism that dynamically adjusts resource distribution based on observed performance trends during optimization.

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