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 ...

Journal of Computational Mathematics, Vol. 31, No. 4 (July 2013), pp. 335-354 (20 pages) In this paper, we consider the solution of the standard linear programming (LP). A remarkable result in LP ...

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 ...

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 ...

Machine learning is hard. Algorithms in a particular use case often either don't work or don't work well enough, leading to some serious debugging. And finding the perfect algorithm–the set of rules a ...

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 ...