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package edu.stanford.nlp.optimization;

/**
 * The interface for unconstrained function minimizers.
 * 
 * Implementations may also vary in their requirements for the
 * arguments.  For example, implementations may or may not care if the
 * initial feasible vector turns out to be non-feasible
 * (or null!).  Similarly, some methods may insist that objectives
 * and/or constraint Function objects actually be
 * DiffFunction objects.
 *
 * @author Dan Klein
 * @version 1.0
 * @since 1.0
 */
public interface Minimizer {

  /**
   * Attempts to find an unconstrained minimum of the objective
   * function starting at initial, within
   * functionTolerance.
   *
   * @param function          the objective function
   * @param functionTolerance a double value
   * @param initial           a initial feasible point
   * @return Unconstrained minimum of function
   */
  double[] minimize(T function, double functionTolerance, double[] initial);
  double[] minimize(T function, double functionTolerance, double[] initial, int maxIterations);

}