To mitigate the pain of manually tuning hyperparameters of deep neural networks,
automated machine learning (AutoML) methods have been developed to search for an …

Two supervised learning algorithms, a basic neural network and a long short‐term memory
recurrent neural network, are applied to traffic including DDoS attacks. The joint effects of …

Deep learning researchers and practitioners often struggle to find an optimal set of
hyperparameters to maximize model performance due to a large combinatorial search …

Hyper-parameter optimization is crucial for pushing the accuracy of a deep learning model
to its limits. However, a hyper-parameter optimization job, referred to as a study, involves …

Assessing advertisements, specifically on the basis of user preferences and ad quality, is
crucial to the marketing industry. Although recent studies have attempted to use deep neural …

In this paper, we present accuracy-time efficient hyperparameter optimization (HPO) using
advantage actor-critic (A2C)-based reinforcement learning (RL) and early stop** in …

In modern cloud computing environments, ephemeral cloud resources are becoming
increasingly prevalent. Ephemeral resources exhibit two distinct characteristics:(1) they can …

Hyper-parameter optimization is crucial for pushing the accuracy of a deep learning model
to its limits. A hyper-parameter optimization job, referred to as a study, involves numerous …

In a method for AI model optimization, an optimization device receives an original AI model
and search configuration information that comprises a plurality of search items each …