Duration: 4 hours. This module will cover integer linear programming and its use in solving NP-hard (combinatorial optimization) problems. We will cover some examples of what integer linear ...

COMP_SCI 396, 496: Advanced Algorithm Design through the Lens of ... examines such topics as greedy algorithms, dynamic programming, graph algorithms, string processing, and algorithms for ...

The new AI program can recognize a handwritten character about as accurately as a human can, after seeing just a single example. The best existing machine-learning algorithms,… ...

1 Describe key models of computation and associated programming language paradigms based on them.; 2 Evaluate the advantages and disadvantages of various programming languages for different ...

The graph below shows the total number of publications each year in Probabilistic Programming and Inference Algorithms. References [1] On the hardness of analysing probabilistic programs .

K. Deb, Nonlinear Goal Programming Using Multi-Objective Genetic Algorithms, The Journal of the Operational Research Society, Vol. 52, No. 3 (Mar., 2001), pp. 291-302 Free online reading for over 10 ...

Programming and prejudice: Computer scientists discover how to find bias in algorithms. ScienceDaily . Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2015 / 08 / 150814193120.htm ...

Xin-wei Liu, Ya-xiang Yuan, A ROBUST TRUST REGION ALGORITHM FOR SOLVING GENERAL NONLINEAR PROGRAMMING, Journal of Computational Mathematics, Vol. 19, No. 3 (May 2001), pp. 309-322 Free online reading ...