Army scientists train machine learning models to wrangle dirty data

Army researchers have developed a new approach for training machine learning models that can better withstand dirty and deceptive data. Models trained under this method have greatly surpassed other state-of-the-art models in terms of robustness, scientists said. Machines outperform humans in many data-processing tasks, but sometimes fall victim to obvious mistakes that humans can see a mile away. Scientists at the U.S. Army Combat Capabilities Development Command's Army Research Laboratory designed a new approach that makes it harder for adversaries to trick machine learning models. "We were able to reduce model complexity by about a factor of 10 without affecting other performance metrics under benign conditions," said Army scientist Dr. Ananthram Swami.