The course introduces basic data structures ... efficient algorithms, choosing the most appropriate solutions for their future projects. Introduction and basic definitions: algorithm, problem, ...

A recently developed methodology in this field is small-variance asymptotic analysis, a mathematical technique for deriving learning algorithms that capture ... time evolution in the latent structure ...

Abstract: Multifeature learning has been a fundamental research problem in multimedia analysis. Most existing multifeature ... correlation variation between nearby data pairs. Second, in most existing ...

On completion of the module, students will be able to demonstrate: a knowledge of common data structures and their relative advantages and disadvantages familiarity with common algorithmic techniques ...

In the past, topics have included: the field of statistics and its history, large-scale sample surveys, survival analysis ... masters students in Statistics & Data Science. Topics include important ...

What do Sudoku, AI, Rubik’s cubes, clocks and molecules have in common? They can all be reimagined as algebraic equations.

Neurosymbolic AI combines the learning of LLMs with teaching the machine formal rules that should make them more reliable and ...

Proteins are among the most studied molecules in biology, yet new research from the University of Göttingen shows they can ...

The Databricks Inc.- and Snowflake Inc.-backed startup says its new Unstructured Data Monitoring tool gives enterprises an ...