Dynamic programming (DP) algorithms have become indispensable in computational biology, addressing problems that range from sequence alignment and phylogenetic inference to RNA secondary structure ...

When the FORTRAN programming language debuted in 1957, it transformed how scientists and engineers programmed computers.

In this Artificial Intelligence podcast with Lex Fridman, computer scientist Donald Knuth discusses Alan Turing, Neural networks, machine learning and other AI topics from ant colonies and human ...

Probabilistic programming has emerged as a powerful paradigm that integrates uncertainty directly into computational models. By embedding probabilistic constructs into conventional programming ...

https://doi.org/10.2307/2582400 • https://www.jstor.org/stable/2582400 Copy URL This paper offers a new approach to the solution of zero-one goal-programming ...

When James Gosling isn’t preaching Java’s virtues, he spends his days in a quiet corner office at Sun Labs, dreaming up new ways to help programmers manage complexity. With the Star Trek Borg mask he ...

In the field of computer science, there is perhaps no more fundamental task than to sort. Bubble, heap, merge—take your pick. The methods for reordering data inside a computer have been theorized to ...

An example of the quadratic assignment problem (QAP) is the facility location problem, in which n facilities are assigned, at minimum cost, to n sites. Between each pair of facilities, there is a ...

Have you ever wondered if there is a correlation between a computer’s energy consumption and the choice of programming languages? Well, a group of Portuguese university researchers did and set out to ...