Priya Ranjan works at the intersection of computational biology and bioinformatics, focusing on plant-microbe interactions, ...

In today’s digital era, financial institutions face unprecedented challenges in safeguarding their assets and customer information. With cyberattacks evolving both ...

In this paper, we explore the applicability of selected machine learning models to classify incoming flows as elephants or mice on the first packet, using Internet Protocol (IP) and transport layer ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

Amid all the hype and hysteria about ChatGPT, Bard, and other generative large language models (LLMs), it’s worth taking a step back to look at the gamut of AI algorithms and their uses.After ...

But until recently, machine learning has often been unable to draw conclusions from ever larger collections of text—not least because certain aspects of historical documents (in Preiser-Kapeller ...

In many scientific endeavors, increasingly abstract representations of data allow for new interpretive methodologies and conceptualization of phenomena. For example, moving from raw imaged pixels to ...