Class Schedule : M T Th 14:00-15:00 L10
Exam Schedule: Please check http://www.iitk.ac.in/doaa/data/endsemester2015161.pdf
Syllabus:
Some topics from the glossary: http://alumni.media.mit.edu/~tpminka/statlearn/glossary/
Useful Links:
http://www.shivani-agarwal.net/Teaching/Misc/Learning-Theory/Aug-2014/index.html
http://www.idiap.ch/~marcel/professional/Lectures_and_Labs.html
http://www.idiap.ch/~marcel/professional/EPFL_2015.html
Topics:
The Parzen window estimate of a pdf (thin black line) matches with the actual pdf (thicker blue line). The histogram of the actual data points are shown in light gray in the background.
Papers:
The use of multiple measurements in taxonomic problems by R. A. Fisher
On the generalized distance in statistics by P. C. Mahalanobis
OPTIMAL SMOOTHING IN KERNEL DISCRIMINANT ANALYSIS
ON ERROR-RATE ESTIMATION IN NONPARAMETRIC CLASSIFICATION
Choice of neighbor order in nearest-neighbor classification
Geometric representation of HDLSS data
Consistency of kNN (check p.2 onwards)
Video lectures:
Books:
Text:
1. Pattern Classification by Richard Duda, Peter Hart and David Stork , John Wiley & Sons, 2001.
References:
2. A Probabilistic Theory of Pattern Recognition by Luc Devroye, László Györfi and Gábor Lugosi.
3. The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, Jerome Friedman.
4. Multivariate Density Estimation by David W. Scott
List: http://homepages.inf.ed.ac.uk/rbf/IAPR/researchers/MLPAGES/mlbks.htm
Notes:
Assignments:
Exams:
Assignments will be given, and discussed in the class (if necessary). However, no grading for assignments.
Mark for each exam is stated in brackets.
The exact date of the quiz will not be announced in advance.
Quiz 1 : [10] week starting August 17
Mid-sem : [30] September 20 [one question in statistics]
Quiz 2 : [10] week starting October 12
Assignment 3 : [10] November 5 and 7
Quiz 3 : [10] week starting November 9
End-sem : [45] November 19, 16:00-19:00
Final Score = (5/6)*Mid-sem + Best of two quizzes + Assignment 3 + End-sem
Grading:
A - E : based on score quantiles
F : if score is less than or equal to 25 out of 100 [no exceptions]
For obtaining an 'A' grade, I encourage you to answer atleast one of the two questions in statistics.
Highest mark scorer in each exam gets a 'prize'.
All the best!