Topics in Machine Learning and Optimization

Topics in Machine Learning and Optimization

Internship Description

Topics in machine learning (ML). The project can be of a theoretical nature (e.g., design of optimization algorithms for training ML models; building foundations of deep learning; distributed, stochastic and nonconvex optimization), or of a practical nature (e.g., creative application and modification of existing techniques to problems in federated learning, computer vision, health, robotics, engineering). The precise topic will be decided together with the successful applicants, and will be tailored to their skills and background.

Deliverables/Expectations

Original research – contribution to a research paper​.

Faculty Name

Peter Richtarik

Field of Study

Computer Science, Mathematics or a related discipline