Hyperparameter optimization constitutes a large part of typical modern machine learning
(ML) workflows. This arises from the fact that ML methods and corresponding preprocessing …

In recent years, research in applying optimization approaches in the automatic design of
deep neural networks has become increasingly popular. Although various approaches have …

Fully miniaturized robots (eg, drones), with artificial intelligence (AI)-based visual navigation
capabilities, are extremely challenging drivers of Internet-of-Things edge intelligence …

Classifying and counting vehicles in road traffic has numerous applications in the
transportation engineering domain. However, the wide variety of vehicles (two-wheelers …

During the last years, research in applying optimization approaches in the automatic design
of deep neural networks (DNNs) becomes increasingly popular. Although various …

One of the key challenges in designing machine learning systems is to determine the right
balance amongst several objectives, which also oftentimes are incommensurable and …

Efficient HPC libraries often expose multiple tunable parameters, algorithmic
implementations, or a combination of them, to provide optimized routines. The optimal …

Emerging applications such as Deep Learning are often data-driven, thus traditional
approaches based on auto-tuners are not performance effective across the wide range of …

Hand gestures for speech impaired community have their usage for specific language. In
Indonesia, hand gesture has their natural two hands sign and widely accepted usage …

The design of machine learning systems often requires trading off different objectives, for
example, prediction error and energy consumption for deep neural networks (DNNs) …