We present a general model for set systems to be independence families with respect to set families which determine classes of proper weight functions on a ground set. Within this model, matroids arise from a natural subclass and can be characterized by the optimality of the greedy algorithm. ...
Method: n_last Divides the data into a specified number of groups. The algorithm finds the most equal group sizes possible, using all data points. Only the last group is able to differ in size. E.g. group sizes: 11, 11, 11, 11, 13 Method: n_rand Divides the data into a specified...
Our experiments show that our method diff is faster than linear in most cases, whilst using more space. The UNIX diff command is based on the greedy algorithm by Myers and Miller [11] for the unit cost function. Since their algorithm fills the values of the dynamic programming table in ...
Thus the compressor uses a greedy algorithm for building the dictionary. The optimal algorithm would consider all possible dictionaries and their effect on compression, but this would be prohibitively time-consuming. To perform dictionary encoding, the compressor uses a order-1 semi-static Markov ...
[41] proposed a generalization privacy-preserving method suitable for the scenarios of 1:M records (an individual can have multiple records) with multiple sensitive attributes. Temuujin et al. [42] developed a more efficient l-diversity algorithm for preserving privacy of dynamically published ...
And, a generalized SAS macro can generate optimized N:1 propensity score matching of subjects assigned to different groups using the radius method. Matching can be optimized either for the number of matches within the maximum allowable radius or by the closeness of the matches within the radius....
and analyze a method based on the Frank–Wolfe algorithm for their solution. Under suitable conditions on the behavior of the method, we establish global and local convergence properties. However, difficulties may arise when a certain submatrix loses rank, and we describe a technique for dealing ...
| with the greedy algorithm. The first proof is from Johnson [20]. Lov´ asz [23] obtained the same factor with a different method. Later, Chv´ atal extended the result to the weighted set cover problem [8], in which the subsets S ...
An Improved Greedy Reduction Algorithm Based on Neighborhood Rough Set Model for Sensors Screening of Exoskeleton The reasonable selection of sensors is essential for sensor fusion for gait recognition, and this paper proposes a reduction method based on an improved gr... Z Qi,Y Liu,Q Song,......
This approach makes the framework easily applicable to many combinatorial optimization problems without any change in the method and given the proper training step for each problem separately. The training process of DRLH makes it adaptable to different problem conditions and settings, and ensures that...