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.

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 ...

Dynamic programming (DP) algorithms have become indispensable in computational biology, addressing problems that range from sequence alignment and phylogenetic inference to RNA secondary structure ...

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.

Because assembly lacks the formal structures and abstractions of higher-level programming, and because a single mistake can cause the algorithm to break, the game that the AI must play is no fun.

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

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 ...

Using machine learning, MIT CSAIL, and Project CETI, researchers revealed complex, language-like structures in sperm whale communication with context-sensitive and combinatorial elements. Credit ...

From predicting who will be a repeat offender to who’s the best candidate for a job, computer algorithms are now making complex decisions in lieu of humans. But increasingly, many of these algorithms ...