Parallel and Stochastic optimization of Conditional Random Field for optical character recognition (OCR)
a) Implementation of parallel optimization algorithm based on the LBFGS solver provided by PETSc, leveraging its parallel primitives and testing the scalability on cluster.
b) Implementation of stochastic gradient solvers (SGD and ADAM), and test their efficiency in comparison with LBFGS.