We consider the problem of obtaining the approximate maximum a posteriori estimate of a discrete random field characterized by pairwise potentials that form a truncated convex mod...
To obtain classification systems with both good generalizat`ion performance and efficiency in space and time, we propose a learning method based on combinations of weak classifiers...
In recent years, interest in studying evolutionary algorithms (EAs) for dynamic optimization problems (DOPs) has grown due to its importance in real-world applications. Several app...
We study the random m-ary search tree model (where m stands for the number of branches of the search tree), an important problem for data storage in computer science, using a varie...
Satya N. Majumdar, David S. Dean, Paul L. Krapivsk...
We analyze the addition of a simple local improvement step to various known randomized approximation algorithms. Let ' 0:87856 denote the best approximation ratio currently k...