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Consider the simple version of the problem, with k = 1, where all clients are to agree on a single site for an object O. Approaching the problem naively, it might appear sufficient to treat the n sites as buckets in a hash table and hash the object name O into this table. Unfortunately, if any of the sites fails or is unreachable, the hash ...
This algorithm can easily be adapted to compute the variance of a finite population: simply divide by n instead of n − 1 on the last line.. Because SumSq and (Sum×Sum)/n can be very similar numbers, cancellation can lead to the precision of the result to be much less than the inherent precision of the floating-point arithmetic used to perform the computation.
For example, the weighted estimator proposed by Cohen et al. [5] can be obtained when the continuous max sketches estimator is extended to solve the weighted problem. In particular, the HyperLogLog algorithm [6] can be extended to solve the weighted problem. The extended HyperLogLog algorithm offers the best performance, in terms of statistical ...
The hedge algorithm is similar to the weighted majority algorithm. However, their exponential update rules are different. [2] It is generally used to solve the problem of binary allocation in which we need to allocate different portion of resources into N different options. The loss with every option is available at the end of every iteration.
Interval scheduling is a class of problems in computer science, particularly in the area of algorithm design. The problems consider a set of tasks. The problems consider a set of tasks. Each task is represented by an interval describing the time in which it needs to be processed by some machine (or, equivalently, scheduled on some resource).
Hasse diagram of some classes of quantitative automata, ordered by expressiveness. [1]: Fig.1 In theoretical computer science and formal language theory, a weighted automaton or weighted finite-state machine is a generalization of a finite-state machine in which the edges have weights, for example real numbers or integers.
In this graph, the widest path from Maldon to Feering has bandwidth 29, and passes through Clacton, Tiptree, Harwich, and Blaxhall. In graph algorithms, the widest path problem is the problem of finding a path between two designated vertices in a weighted graph, maximizing the weight of the minimum-weight edge in the path.
The tree with the minimal weighted path length is, by definition, statically optimal. But weighted path lengths have an interesting property. Let E be the weighted path length of a binary tree, E L be the weighted path length of its left subtree, and E R be the weighted path length of its right subtree. Also let W be the sum of all the ...