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

He is the author of the multi-volume work, the magnum opus, The Art of Computer Programming. He made several key contributions to the rigorous analysis of the computational complexity of algorithms.

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 ...

Unlike dynamic programming approaches whose performance relies heavily on the degree of discretization applied to the data, our algorithm does not suffer from such space-complexity issues.

GCSE Computer Science Computational thinking, algorithms and programming learning resources for adults, children, parents and teachers.

The algorithm successfully identified causal links in every case, compared with most methods that can only handle some cases.

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

It is worth mentioning that an efficient solution of the problem considered in the example is also obtained using Multiobjective Genetic Algorithm (MOGA) which alongwith the sufficiency conditions ...

Research from all publishers Recent work in probabilistic programming has sought to address both theoretical and computational challenges. For example, investigations into the intrinsic complexity ...