9. A method for enhancing the performance of a trained recognizer for an individual, the method comprising: retraining, by one or more computing devices configured to enhance the performance of the trained recognizer for the individual, the trained recognizer based at least in part upon at least one sample personalized to the individual using regularization biased to a base state of the trained recognizer; determining a new state of the trained recognizer based upon the regularization and the at least one personalized sample; and updating the trained recognizer, the determining of the new state of the trained recognizer further comprises: determining a distance between the base state of the trained recognizer and a possible state of the trained recognizer; determining risk for the at least one personalized sample using the possible state of the trained recognizer; and minimizing the distance and the risk.
9. A method for enhancing the performance of a trained recognizer for an individual, the method comprising: retraining, by one or more computing devices configured to enhance the performance of the trained recognizer for the individual, the trained recognizer based at least in part upon at least one sample personalized to the individual using regularization biased to a base state of the trained recognizer; determining a new state of the trained recognizer based upon the regularization and the at least one personalized sample; and updating the trained recognizer, the determining of the new state of the trained recognizer further comprises: determining a distance between the base state of the trained recognizer and a possible state of the trained recognizer; determining risk for the at least one personalized sample using the possible state of the trained recognizer; and minimizing the distance and the risk. 11. The method of claim 9 , retraining the trained recognizer is based at least in part on a weight for the at least one personalized sample, the weight based in part on the likelihood of recognition error for the personalized sample.