Least squares problem. Unconstrained Optimization: gradient
descent with backtracking, Newton method; constrained
optimization: primal-dual Newton, interior point methods; linear
programming. Inference and Learning Algorithms: sampling
algorithms, Monte-Carlo method, importance sampling, stochastic
optimization; regression, classification, clustering. Other topics
as chosen by the instructor.