| Line 1: | Line 1: | ||
| − | + | <br> | |
| − | + | ||
| − | + | ||
| − | + | ||
| + | <br> | ||
| − | + | == [[ECE662]]: '''Statistical Pattern Recognition and Decision Making Processes, Spring 2014''' (cross-listed with CS662) == | |
| − | == [[ECE662]]: '''Statistical Pattern Recognition and Decision Making Processes, Spring 2014''' | + | |
---- | ---- | ||
<div style="border-bottom: rgb(68,68,136) 1px solid; border-left: rgb(51,51,136) 4px solid; padding-bottom: 2em; margin: auto; padding-left: 2em; width: 30em; padding-right: 2em; background: rgb(238,238,255); border-top: rgb(68,68,136) 1px solid; border-right: rgb(68,68,136) 1px solid; padding-top: 2em"> | <div style="border-bottom: rgb(68,68,136) 1px solid; border-left: rgb(51,51,136) 4px solid; padding-bottom: 2em; margin: auto; padding-left: 2em; width: 30em; padding-right: 2em; background: rgb(238,238,255); border-top: rgb(68,68,136) 1px solid; border-right: rgb(68,68,136) 1px solid; padding-top: 2em"> | ||
== '''Welcome to ECE662!''' == | == '''Welcome to ECE662!''' == | ||
| + | |||
*When you see the peer review of your work in your dropbox, do not click "mark as read". If you do, then the review will disappear. | *When you see the peer review of your work in your dropbox, do not click "mark as read". If you do, then the review will disappear. | ||
</div> | </div> | ||
| Line 16: | Line 14: | ||
== '''Course Information''' == | == '''Course Information''' == | ||
| + | |||
Instructor: | Instructor: | ||
| − | *[[User:Mboutin|Professor Mimi Boutin]] | + | |
| − | ::Office: MSEE342 | + | *[[User:Mboutin|Professor Mimi Boutin]] |
| − | ::[[ | + | |
| + | ::Office: MSEE342 | ||
| + | ::[[Open office hours mboutin|Office hours]] | ||
::[https://www.projectrhea.org/rhea/index.php/Special:DropBox?forUser=mboutin&assn=true Assignment Drop Box] | ::[https://www.projectrhea.org/rhea/index.php/Special:DropBox?forUser=mboutin&assn=true Assignment Drop Box] | ||
| + | |||
Lecture: | Lecture: | ||
| + | |||
*'''When?''' TuTh, 10:30 - 11:45 | *'''When?''' TuTh, 10:30 - 11:45 | ||
*'''Where?''' EE117 (subject to change) | *'''Where?''' EE117 (subject to change) | ||
| + | |||
---- | ---- | ||
| − | ==[https://www.projectrhea.org/learning/slectures.php Slectures]== | + | |
| − | Please use this [[ | + | == [https://www.projectrhea.org/learning/slectures.php Slectures] == |
| − | *Slectures on Probability and Statistics | + | |
| − | **[[ | + | Please use this [[Slecture template ECE662S14|template for text slectures]] or this [[Slecture template video ECE662S14|template for video slectures]] |
| − | **[[ | + | |
| − | **[[PCA|Principal Component Analysis (PCA)]], by [http://web.ics.purdue.edu/~zhou338/ Tian Zhou] | + | *Slectures on Probability and Statistics |
| − | *Slectures on Bayes Rule | + | **[[ECE662 Whitening and Coloring Transforms S14 MH|Whitening and Coloring Transforms]], by [[User:Mhossain|Maliha Hossain]] |
| − | **[[ | + | **[[How to generate random n dimensional data from two categories with different priors slecture Minwoong Kim ECE662 Spring 2014|How to generate n-D Gaussian data in the two category case ]], by Minwoong Kim (in Korean) |
| − | **[[ | + | **[[PCA|Principal Component Analysis (PCA)]], by [http://web.ics.purdue.edu/~zhou338/ Tian Zhou] |
| − | **[[ | + | *Slectures on Bayes Rule |
| − | **[[ | + | **[[From Bayes Theorem to Pattern Recognition via Bayes Rule|From Bayes' Theorem to Pattern Recognition via Bayes' Rule]] by [http://varunvasudevan.com/ Varun Vasudevan] |
| − | **[[ | + | **[[Upper Bounds for Bayes Error|Upper Bounds for Bayes Error]] by G. M. Dilshan Godaliyadda |
| − | **Link to slecture (use a descriptive title) | + | **[[Test|Upper Bounds for Bayes Error (including the derivation of Chernoff Distance)]] by Jeehyun Choe |
| − | *Slectures on Density Estimation | + | **[[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 |
| + | **Link to slecture (use a descriptive title) | ||
| + | *Slectures on Density Estimation | ||
| + | **[[Mle tutorial|Tutorial on Maximum Likelihood Estimates]] by Sudhir Kylasa | ||
| + | **[[Introduction_to_local_density_estimation_methods|Introduction to local (nonparametric) density estimation methods]] by Yu Liu | ||
*Slectures on Linear Classifiers | *Slectures on Linear Classifiers | ||
---- | ---- | ||
| − | ==Peer Reviews== | + | |
| − | *[[ | + | == Peer Reviews == |
| − | * Heads up: peer review of hw2 will be due April 29 | + | |
| + | *[[Instructions peer review hw1|Instruction for peer reviewing HW1]] | ||
| + | *Heads up: peer review of hw2 will be due April 29 | ||
| + | |||
---- | ---- | ||
| − | == Discussion | + | |
| + | == Discussion == | ||
| + | |||
Feel free to use the space below for discussion, or create a page for discussion and link it below. | Feel free to use the space below for discussion, or create a page for discussion and link it below. | ||
| − | *[[ | + | |
| − | *[[ | + | *[[Data discussion HW1 ECE662 S14 Boutin|Where to find data for HW1]] |
| − | *[[ | + | *[[Yelp Dataset|Possible Real-world data to use for class]] |
| + | *[[Programming help ECE662S14|Programming help!]] | ||
*New Discussion | *New Discussion | ||
| + | |||
---- | ---- | ||
| − | [[ECE662|Back to main ECE662 page]] | + | |
| + | [[ECE662|Back to main ECE662 page]] | ||
| + | |||
| + | [[Category:ECE662Spring2014Boutin]] [[Category:ECE]] [[Category:ECE662]] [[Category:Pattern_recognition]] | ||
Revision as of 18:59, 15 April 2014
Contents
ECE662: Statistical Pattern Recognition and Decision Making Processes, Spring 2014 (cross-listed with CS662)
Welcome to ECE662!
- When you see the peer review of your work in your dropbox, do not click "mark as read". If you do, then the review will disappear.
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
- Slectures on Bayes Rule
- From Bayes' Theorem to Pattern Recognition via Bayes' Rule by Varun Vasudevan
- Upper Bounds for Bayes Error by G. M. Dilshan Godaliyadda
- Upper Bounds for Bayes Error (including the derivation of Chernoff Distance) by Jeehyun Choe
- Bayes Rule to minimize risk, by Andy Park
- Bayes Rule for Minimizing Risk by Dennis Lee
- Link to slecture (use a descriptive title)
- Slectures on Density Estimation
- Tutorial on Maximum Likelihood Estimates by Sudhir Kylasa
- Introduction to local (nonparametric) density estimation methods by Yu Liu
- Slectures on Linear Classifiers
Peer Reviews
- Instruction for peer reviewing HW1
- Heads up: peer review of hw2 will be due 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
