This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving algorithmic problems that seek optimal ...

It covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) .

Advanced study in models of computation, programming languages and algorithms with a specific focus on concurrent programming. The course includes models of computation, programming language paradigms ...

In an earlier paper [20] combinatorial programming procedures were presented for solving a class of integer programming problems in which all elements are zero or one. By representing the problem ...

The plan provides opportunities for study in software systems, algorithms and complexity, machine architecture, computer graphics, programming languages, machine learning, and other core areas of ...

Probabilistic Programming and Inference Algorithms Publication Trend The graph below shows the total number of publications each year in Probabilistic Programming and Inference Algorithms.

Daniel R. Jiang, Warren B. Powell, An Approximate Dynamic Programming Algorithm for Monotone Value Functions, Operations Research, Vol. 63, No. 6 (November-December 2015), pp. 1489-1511 ...

Introduction to theory of algorithms and basics of Python programming. Algorithmic thinking: Do you know how to multiply integers? Basic toolkit for the design and analysis of algorithms, and an ...

Introduction to theory of algorithms and basics of Python programming. Algorithmic thinking: Do you know how to multiply integers? Basic toolkit for the design and analysis of algorithms, and an ...