| Line 49: | Line 49: | ||
***Upper Bounds for Bayes Error by Yihan Ding{{Upper Bounds for Bayes error}} | ***Upper Bounds for Bayes Error by Yihan Ding{{Upper Bounds for Bayes error}} | ||
***[[Test|Text slecture in English (includes the derivation of Chernoff Distance)]] by Jeehyun Choe | ***[[Test|Text slecture in English (includes the derivation of Chernoff Distance)]] by Jeehyun Choe | ||
| − | **[[Slecture Bayes rule to minimize risk Andy Park ECE662 Spring 2014|Bayes Rule to minimize risk]], by Andy Park | + | **Bayes Rule to Minimize Risk |
| − | **[[Bayes Rule Minimize Risk Dennis Lee|Bayes Rule for Minimizing Risk]] by Dennis Lee | + | ***[[Slecture Bayes rule to minimize risk Andy Park ECE662 Spring 2014|Bayes Rule to minimize risk]], by Andy Park |
| − | + | ***[[Bayes Rule Minimize Risk Dennis Lee|Bayes Rule for Minimizing Risk]] by Dennis Lee | |
| − | **[[Bayes rule in practice]] by Lu Wang | + | **[[Bayes rule in practice]] by Lu Wang |
| − | + | ||
*Slectures on Neyman-Pearson test and ROC curves | *Slectures on Neyman-Pearson test and ROC curves | ||
**[[Slecture Neyman-Pearson Lemma and Receiver Operating Characteristic Curve ECE662Spring2014]] by Soonam Lee | **[[Slecture Neyman-Pearson Lemma and Receiver Operating Characteristic Curve ECE662Spring2014]] by Soonam Lee | ||
*Slectures on Density Estimation | *Slectures on Density Estimation | ||
| − | **[[Mle tutorial|Tutorial on Maximum Likelihood Estimates]] by Sudhir Kylasa | + | **Maximum Likelihood Estimation (MLE) |
| − | **[[Introduction to local density estimation methods|Introduction to local (nonparametric) density estimation methods]] by [https://www.youtube.com/watch?v=WwPpsLjUsfQ Yu Liu] | + | ***[[Mle tutorial|Tutorial on Maximum Likelihood Estimates]] by Sudhir Kylasa |
| + | **Introduction to Local density Estimation Techniques (so-called "non-parametric") | ||
| + | ***[[Introduction to local density estimation methods|Introduction to local (nonparametric) density estimation methods]] by [https://www.youtube.com/watch?v=WwPpsLjUsfQ Yu Liu] | ||
*Slectures on Linear Classifiers | *Slectures on Linear Classifiers | ||
Revision as of 10:49, 24 April 2014
Contents
ECE662: Statistical Pattern Recognition and Decision Making Processes, Spring 2014 (cross-listed with CS662)
Welcome to ECE662!
- Reviews for HW2 are activated. Please complete your review before class on Tuesday April 29.
- Does anybody in the class speak Spanish (besides Francis)? If so, please send me an email. -pm
- Does anybody in the class speak Russian (besides Aziza)? If so, please send me an email. -pm
Course Information
Instructor:
- Office: MSEE342
- Office hours
- Assignment Drop Box
Lecture:
- When? TuTh, 10:30 - 11:45
- Where? EE117 (subject to change)
Slectures
Please use this template for text slectures or this template for video slectures
- Slectures on Probability and Statistics
- Whitening and Coloring Transforms, by Maliha Hossain
- How to generate n-D Gaussian data in the two category case , by Minwoong Kim (in Korean)
- Principal Component Analysis (PCA), by Tian Zhou
- Curse of Dimensionality, by Haonan Yu
- Slectures on Bayes Rule
- Derivation of Bayes Rule
- Text slecture in English by Varun Vasudevan
- Video slecture in English by Nadra Guizani
- Upper Bounds for Bayes Error
- Upper Bounds for Bayes Error by G. M. Dilshan Godaliyadda
- Upper Bounds for Bayes Error by Yihan Ding www.projectrhea.org/rhea/index.php/Upper_Bound_for_Bayes_error
- Text slecture in English (includes the derivation of Chernoff Distance) by Jeehyun Choe
- Bayes Rule to Minimize Risk
- Bayes Rule to minimize risk, by Andy Park
- Bayes Rule for Minimizing Risk by Dennis Lee
- Bayes rule in practice by Lu Wang
- Derivation of Bayes Rule
- Slectures on Neyman-Pearson test and ROC curves
- Slectures on Density Estimation
- Maximum Likelihood Estimation (MLE)
- Tutorial on Maximum Likelihood Estimates by Sudhir Kylasa
- Introduction to Local density Estimation Techniques (so-called "non-parametric")
- Maximum Likelihood Estimation (MLE)
- Slectures on Linear Classifiers
Peer Reviews
- Instruction for peer reviewing HW1
- Instruction for peer reviewing HW2 (due before class on April 29)
Discussion
Feel free to use the space below for discussion, or create a page for discussion and link it below.
- Where to find data for HW1
- Possible Real-world data to use for class
- Programming help!
- New Discussion
