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

This is an advanced undergraduate course on algorithms. This course examines such topics as greedy algorithms, dynamic programming, graph algorithms, string processing, and algorithms for ...

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 ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

This is a preview. Log in through your library . Abstract A unifying framework is developed to facilitate the understanding of most known computational approaches to integer programming. A number of ...

Researchers from MIT, Arizona State University and Baylor University have developed a new algorithm that promises to simplify the arduous and complex task of assembling DNA into structures other than ...

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 ...

[Kory] has been writing genetic algorithms for a few months now. This in itself isn’t anything unique or exceptional, except for what he’s getting these genetic algorithms to do. [Kory] has been using ...