public void learn(double epsilon,int iterLimit){
  ProximalGradient pg=new ProximalGradient();
  setParams(new MGMParams(pg.learnBackTrack(this,params.toMatrix1D(),epsilon,iterLimit),p,lsum));
}

public void learn ( double epsilon , int iterLimit ) { ProximalGradient pg = new ProximalGradient ( ) ; setParams ( new MGMParams ( pg . learnBackTrack ( this , params . toMatrix1D ( ) , epsilon , iterLimit ) , p , lsum ) ) ; }
learn mgm traditional way with objective function tolerance . recommended for inference applications that need accurate pseudolikelihood
