Learn what a randomized algorithm is, how it differs from a deterministic algorithm, what are some common types of randomized algorithms, and how you can use them in your code.

Learn about the most effective methods for parallelizing randomized algorithms, such as Monte Carlo, Las Vegas, load balancing, consensus, and testing.

A new theorem regarding the robust-stability hypercube-tolerance with respect to the specific system defined by the middle-point of a hyper-cube and a given stabilizing static-output-feedback for it, ...

Other algorithms, such as Peres's and Elias's extract maximum entropy (randomness) from an input, however, the input for their algorithms must be a fixed number of input bits and not a streaming input ...

Output 5.7.1: Arc Routing: Default Layout Next, a different routing of the arcs is obtained by specifying the DP and the HTRACKS= options. As a result of these options, the NETDRAW procedure uses a ...

Once a particular sequence of functions is identifed to have a significantly larger score than all its counterparts , the program does not generate a random output , it will directly apply the same ...

We describe an algorithm based on several novel concepts for synthesizing a desired program in this language from input-output examples. The synthesis algorithm is very efficient taking fraction of a ...

In any iteration, the random sample is encoded as a quantum state, and a series of quantum operations are applied to it to produce an output state that can be measured to generate the new sample.

We propose a novel output-oriented program synthesis algorithm to automate API usage adaptations via program transformation. Our aim is not only to rely on the few example human adaptations of the ...