The bookshelf problem (which computer scientists call the “list labeling” problem) is one of the most basic topics in the field of data structures. “It’s the kind of problem you’d teach to freshman or ...

Some types of predictive analytics software use machine learning to revise algorithms based on learnings from the data collected over time, continuously improving prediction accuracy.

Learn how to document data structures and algorithms effectively, using common tools and techniques, in this system development article.

Algorithms implemented in the Data Structures and Algorithm Complexity discipline.

We present a high-throughput, end-to-end pipeline for organic crystal structure prediction (CSP)─the problem of identifying the stable crystal structures that will form from a given molecule based ...

Formation control plays a fundamental role in many domains, such as autonomous vehicles, aerial vehicles, and robotics, by enabling coordinated movement and cooperation among multiple agents. In this ...

This paper presents a robust exploration of the capabilities of conditional Generative Adversarial Networks (GANs) in harnessing labeled data to produce high-quality labels for unlabeled samples. By ...

Despite decreased incidence rates in average-age onset patients in high-income economies, colorectal cancer is the third most diagnosed cancer in the world, with increasing rates in emerging economies ...

Health information technology (health IT) has potential to improve patient safety but its implementation and use has led to unintended consequences and new safety concerns. A key challenge to ...

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