joint phd mlstat-Machine Learning Department - Carnegie Mellon University

Joint PhD Program in Statistics & Machine Learning

Exciting research is being done at the boundary between Machine Learning and Statistics. This is reflected at Carnegie Mellon by the strong ties between the Machine Learning Department and the Department of Statistics. The Joint Ph.D. Program in Statistics and Machine Learningis a new program aimed at preparing students for academic careers in both CS and Statistics departments at top universities.

This PhD program differs from the ML PhD program in that it places significantly more emphasis on preparation in statistical theory and methodology. Similarly, this program differs from the Statistics PhD program in its emphasis on machine learning and computer science. (See below for a more details on the course requirements.)

Students in this track will be involved in courses and research from both the Departments of Statistics and Machine Learning. During the first year, students will normally be situated in the Department of Statistics. During later years, students will normally be located in the Machine Learning Department unless the primary advisor is in the Department of Statistics. In years 2 and after thesis research co-supervised by a faculty in ML and a faculty in Statistics, or supervised by a joint faculty member. The thesis committee must contain at least one member with home department of Statistics and one with home department of ML.

The typical curriculum is as follows:
(10- designates a ML course. 15- designates a CS course. 36- designates a statistics course.)

* indicates a course that is in the joint program but not in the ML PhD program.
# indicates a course that is in the joint program but not in the Statistics PhD program.

Generally, these courses replace electives in the ML PhD program. The exception is 36-757/758 which serves as the research course 10-920.

FALL - Year One

SPRING - Year One

36-705 Intermediate Statistics #10-702 Statistical Machine Learning
#10-715 Adv. Machine Learning *36-752 Advanced Probability Overview
*36-707 Regression Analysis *36-757 Advanced Data Analysis (ADA) I
#10-915 ML Journal Club

FALL - Year Two

SPRING - Year Two

*36-755 Advanced Statistics One of the following courses:
#10-708 Graphical Models
#10-725 Convex Optimization
#15-826 Multimedia Databases
#15-750 Algorithms or 15-853 Algorithms in the Real World
*36-758 ADA II
*36-750 Statistical Computing (recommended)

Applying to the Joint Program in Statistics & Machine Learning

Students who are interested in the joint Ph.D. program in Statistics and Machine Learning should check the appropriate box on the application either through the Statistics Department or the Machine Learning Department. Admission into this program is decided by a joint committee with faculty from both the Department of Statistics and the Machine Learning Department.

To apply through the Statistics Department, check the box for Joint Statistics/Machine Learning PhD Program. Statistics Online Application

To apply through the Machine Learning Department, check the box for Joint Statistics/Machine Learning PhD Program. Machine Learning Online Application

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