Spring 2014: 550.735 TOPICS IN STATISTICAL PATTERN RECOGNITION
MW @ 3-4:15 @ Hodson 211
Prof. Carey E. Priebe = cep@jhu.edu
"Statistical pattern recognition" is my version of an explicitly prob/stat-centric "machine learning" or "data mining" course, following naturally from 550.630.
This course will focus on theoretical and practical issues in statistical pattern recognition.
We will prove theorems, including universal consistency and arbitrarily slow convergence.
Real problems and data will be considered throughout; both the theory and the practice of classification & clustering are stressed.
I will be teaching out of [DGL] == Devroye, Gyorfi and Lugosi, A Probabilistic Approach to Pattern Recognition, 1996.
Student interest will contribute to topic selection.
* prereqs are prob & stat at the 400 level.
* prob & stat at the 600 level, and stat pat rec at the Duda&Hart level, would be helpful but are not required.