Our new method enables us to extend the range of applicability of the direct optimization method to chromosomes of size comparable to those of bacteria, as well as to datasets with complex combinations of evolutionary events.Combinatorial Pattern Matching: 16th Annual Symposium on Combinatorial Pattern...
simple and easy to implement. It involves sequentially checking each element in a list or array until a match is found or the end of the list is reached. While it may not be the most efficient search algorithm for large datasets, it works well for small to medium-sized collections of ...
The method has, however, proved extremely efficient in practice on datasets that are well beyond the reach of the available provably efficient methods. The program solves several large mtDNA and Y-chromosome instances within a few seconds, giving provably optimal results in times competitive with ...
To verify the performance of the proposed method, a series of experiments on artificial datasets and UCI benchmark datasets are accomplished. Simulation results demonstrate that the proposed method can compete with or outperform the standard...
Knowledge-Based Linear Programming 来自 ACM 喜欢 0 阅读量: 33 作者: Mangasarian,L O.摘要: We introduce a class of linear programs with constraints in the form of implications. Such linear programs arise in support vector machine classification, where in addition to explicit datasets to be ...
We show that our algorithm performs extremely well on large datasets, with peak accuracy approaching that of supervised learning based on Support Vector Machines with large training sets. The method is based on the same idea that underlies Latent Semantic Indexing (LSI). We find a good low-...
Critical parameters in differentiable programming such as random seeds, see Picard [58], dropouts, learning rates, etc. do not exist in the proposed optimization framework. On different datasets competitive performance of the globally optimized sparse MILP neural networks is shown, even though the ...
In the field of genomics, bioinformatics pipelines play a crucial role in processing and analyzing vast biological datasets. These pipelines, consisting of interconnected tasks, can be optimized for efficiency and scalability by leveraging cloud platforms such as Microsoft Azure. The choice ...
We employ a solution algorithm based on a supervised learning technique (a linear regression model of machine-learning) and an integer programming problem and it is applied to the datasets of Winnipeg and Chicago. The regression model ... SA Bagloee,M Sarvi,M Patriksson,... - 《Computer‐...
To demonstrate the effectiveness of our approach, we test our algorithm on public jigsaw datasets and show that it outperforms state-of-the-art methods.doi:4562Rui YuChris RussellLourdes AgapitoComputer ScienceR. Yu, C. Russell, and L. Agapito, "Solving jig- saw puzzles with linear ...