RNN-DAS is an innovative Deep Learning model based on Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) cells, developed for real-time Volcano-seismic Signal Recognition (VSR) using ...

A new family of Android click-fraud trojans leverages TensorFlow machine learning models to automatically detect and interact ...

For our most recent Question of the Week, we asked you about projects you are working on, or have worked on in the past, to ...

In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its applications. Supervised learning is a type of Machine Learning which learns ...

Abstract: This paper investigates the problem of distributed resource management in underwater acoustic communication networks (UACNs) involving multiple transmitters and receivers. In this setting, ...

Large language models have made impressive strides in mathematical reasoning by extending their Chain-of-Thought (CoT) processes—essentially “thinking longer” through more detailed reasoning steps.

With the aim of bridging the gap between laboratory studies and real-world learning experiences, this research investigated the effects of combining retrieval and distributed practice in primary ...

1 School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA. 2 Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA. As cloud ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...