The human brain is often described as a massively parallel ... for tasks lasting two or three minutes. The result is a dataset of around 30 million data points. Georgiou’s work is in determining ...

These neural networks excel at automated feature creation and processing of complex data types like ... DNNs can be applied in parallel and scalable fashion when evaluation is performed on Spark ...

Abstract: We observe that data access and processing takes a significant amount of time in large-scale deep learning training tasks ... on each image, and (3) the frequent communication between ...

Abstract: The models based on deep convolutional networks and recurrent neural networks have dominated in recent image caption generation tasks ... by recent work, by combining the advantages of ...

In this work, we introduce a general-purpose multimodal foundation model BEiT-3, which achieves state-of-the-art transfer performance on both vision and vision-language tasks ... on images (Imglish), ...

Unfortunately, despite their advantages, virtual threads currently lack support in a critical area: direct integration into the stream API, especially in parallel ... tasks based on the system's ...