The machine learning and optimization group works on novel algorithms that allow a computer or robot to learn to infer the most probable state of the world, and to take optimal actions, given noisy or incomplete information. Focus on developing efficient distributed optimization algorithms that are well-suited to current computing technologies. Because we focus on fundamental algorithms, our work has a wide variety of applications spanning a number of other research areas, including computer vision, robotics, human-computer interaction, graphics and materials research.