- Two problem sets.
- There will be a term paper for graduate credit due on the last day of class. The paper should either present some new work addressing a relevant research problem, or provide a critical analysis of 2-3 papers on some aspect of learning, approximation, or networks. A short description of the project you intend to work on is due before Lec #18. Below is a list of available topics; other topics must be approved by the instructor.
List of available projects:
Project 1: Hypothesis Testing with Small Sets.
Project 2: Connection between MED and Regularization.
Project 3: Kernels for Strings.
Project 4: Feature Selection for SVMs: Theory and Experiments.
Project 5: Morphable Models and Roweis’ Nonlinear Dimensionality Reduction.
Project 6: Optimal Bayes Classification Rule and SVMs: Estimation of ROC Curves.
Project 7: IOHMMs: Evaluation of HMMs vs Direct Classifiers like SVMs.
Project 8: Reusing the Test Set: Datamining Bounds.
Project 9: Stability and Generalization.
Project 10: Learning with Very Large Dataset.
Project 11: Bagging, Boosting, and Stability.
Project 12: Local vs. Global Classifiers: Simulations and Use of Prior Knowledge.
Project 13: Invariance to Measure of the RKHS Norm in the Continuum.
Project 14: Concentration Experiments: Dot Products vs Distances in Very High Dimension.
