An algorithm for minimum-error pattern recognition in supervised-learningenvironments
An algorithm for minimum-error pattern recognition in supervised-learningenvironments
Solution of Linear Inequalities
IEEE Transactions on Computers
Pattern Classifier Design by Linear Programming
IEEE Transactions on Computers
Comment on "Pattern Classification Design by Linear Programming"
IEEE Transactions on Computers
An Algorithm for the Solution of Linear Inequalities
IEEE Transactions on Computers
Building a Distance Function for Gestalt Grouping
IEEE Transactions on Computers
Concave programming for minimizing the zero-norm over polyhedral sets
Computational Optimization and Applications
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An algorithm for the optimal solution of consistent and inconsistent linear inequalities is presented, where the optimality criterion is the maximization of the number of satisfied constraints. The algorithm is developed as a nonenumerative search procedure based on two new theorems established in this paper. It is shown that the number of iterative steps before termination is strictly less than that required by an exhaustive search. Experimental results with various types of data establish the computational tractability of the procedure under nontrivial conditions.