A Greedy De ning Set is a set of entries in a Latin square with the property that when the square is systematically lled in with a greedy algorithm, the greedy algorithm succeeds. Let g(n) be the smallest Greedy De ning Set for any Latin square of order n. We give theorems on the upper bounds of g(n) and a table listing upper bounds of g(n) for small values of n. For a circulant Latin square, w...

The problem of influence maximization, i.e., mining top-k influential nodes from a social network such that the spread of influence in the network is maximized, is NP-hard. Most of the existing algorithms for the problem are based on greedy algorithm. Although greedy algorithm can achieve a good approximation, it is computational expensive. In this paper, we propose a totally different approach...

We reinterpret classic Gray codes for binary strings, permutations, combinations, binary trees, and set partitions using a simple greedy algorithm. The algorithm begins with an initial object and an ordered list of operations, and then repeatedly creates a new object by applying the first possible operation to the most recently created object.

We describe the Fast Greedy Sparse Subspace Clustering (FGSSC) algorithm providing an efficient method for clustering data belonging to a few low-dimensional linear or affine subspaces. The main difference of our algorithm from predecessors is its ability to work with noisy data having a high rate of erasures (missed entries with the known coordinates) and errors (corrupted entries with unknown...

This paper proposes a greedy heuristic called Big step greedy heuristic and investigates its application to compute approximate solution for maximum coverage problem. Greedy algorithms construct the solution in multiple steps, the classical greedy algorithm for maximum coverage problem, in each step selects one set that contains the greatest number of uncovered elements. The Big step greedy heu...

This thesis investigates using in line simulation the e ect of non deterministic runtime distributions on the performance of SmartNet s schedule execution using the Opportunistic Load Balancing OLB Algorithm the Limited Best Assignment LBA Algorithm an O mn Greedy Algorithm and an O mn Greedy Algorithm Smart Net is a framework for scheduling jobs and machines in a heterogeneous computing enviro...

We establish signiicantly improved bounds on the performance of the greedy algorithm for approximating minimum set cover and minimum partial cover. Our improvements result from a new approach to both problems. In particular, (a) we improve the known bound on the performance ratio of the greedy algorithm for general covers without cost, showing that it diiers from the classical harmonic bound by...