Thuật ngữ AI
Từ điển đầy đủ về Trí tuệ nhân tạo
Parallel hyperparameter evaluation
Optimization technique where multiple hyperparameter configurations are evaluated simultaneously on different computing units to accelerate the search process.
Distributed grid search
Systematic approach where the search space is partitioned and distributed across multiple computing nodes, each exploring a specific subgrid.
Asynchronous Bayesian optimization
Variant of Bayesian optimization where evaluations do not require synchronization, allowing results to be used as soon as they are available.
Parallel population strategy
Evolutionary optimization method where multiple populations evolve simultaneously on different processors with periodic information exchanges.
Distributed multi-fidelity evaluation
Approach combining high and low fidelity evaluations distributed across different resources to balance computational cost and accuracy.
Parallel genetic algorithm
Parallel implementation of genetic algorithms where selection, crossover, and mutation operations are distributed across multiple processing units.
Distributed simulated annealing
Parallel variant of simulated annealing where multiple Markov chains evolve simultaneously with coordination or independence mechanisms.
Parallel particle swarm optimization
Distributed version of the PSO algorithm where particle movement and updates are computed in parallel on different processors.
Distributed hierarchical multi-armed bandit
Distributed decision-making structure where multiple hierarchical bandits operate in parallel to explore different hyperparameter subspaces.
Distributed meta-learning
Approach where multiple models learn simultaneously on different tasks or data partitions to accelerate hyperparameter optimization.
Adaptive load balancing
Dynamic mechanism distributing hyperparameter evaluations based on the availability and performance of computational resources.
Inter-process communication for optimization
Protocols and interfaces enabling information exchange between parallel optimization processes to coordinate hyperparameter search.
Synchronous batch evaluation
Strategy where a set of hyperparameter configurations is evaluated simultaneously and results are collected before deciding on next evaluations.
Asynchronous continuous evaluation
Approach where new configurations are launched as soon as resources become available, without waiting for ongoing evaluations to complete.
Fault tolerance in distributed optimization
Mechanisms ensuring optimization continuity despite computational node failures or network interruptions.
Cloud resource orchestration for optimization
Automated management of cloud resources (containers, VMs) to optimize dynamic allocation during large-scale hyperparameter optimization.
Parallel sampling strategy
Method that simultaneously generates multiple hyperparameter candidates in parallel, often based on distributed probabilistic models.