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<h2> <a _fcknotitle="true" href="ECE662">ECE662</a>: <b>Statistical Pattern Recognition and Decision Making Processes, Spring 2014</b> (cross-listed with CS662) </h2>
== [[ECE662]]: '''Statistical Pattern Recognition and Decision Making Processes, Spring 2014''' (cross-listed with CS662) ==
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<hr />
 
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----
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<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">
== &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; '''Welcome to ECE662!''' ==
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<h2> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <b>Welcome to ECE662!</b> </h2>
 
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<ul><li>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.
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</li></ul>
 
</div>  
 
</div>  
----
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<hr />
 
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<h2> <b>Course Information</b> </h2>
== '''Course Information''' ==
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<p>Instructor:  
 
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</p>
Instructor:  
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<ul><li><a href="User:Mboutin">Professor Mimi Boutin</a>
 
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</li></ul>
*[[User:Mboutin|Professor Mimi Boutin]]
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<dl><dd><dl><dd>Office: MSEE342  
 
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</dd><dd><a href="Open office hours mboutin">Office hours</a>
::Office: MSEE342  
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</dd><dd><a href="https://www.projectrhea.org/rhea/index.php/Special:DropBox?forUser=mboutin&amp;assn=true">Assignment Drop Box</a>
::[[Open office hours mboutin|Office hours]]
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</dd></dl>
::[https://www.projectrhea.org/rhea/index.php/Special:DropBox?forUser=mboutin&assn=true Assignment Drop Box]
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</dd></dl>
 
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<p>Lecture:  
Lecture:  
+
</p>
 
+
<ul><li><b>When?</b> TuTh, 10:30 - 11:45  
*'''When?''' TuTh, 10:30 - 11:45  
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</li><li><b>Where?</b> EE117 (subject to change)
*'''Where?''' EE117 (subject to change)
+
</li></ul>
 
+
<hr />
----
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<h2> <a href="https://www.projectrhea.org/learning/slectures.php">Slectures</a>  </h2>
 
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<p>Please use this <a href="Slecture template ECE662S14">template for text slectures</a> or this <a href="Slecture template video ECE662S14">template for video slectures</a>
== [https://www.projectrhea.org/learning/slectures.php Slectures] ==
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</p>
 
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<ul><li>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]]
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<ul><li><a href="ECE662 Whitening and Coloring Transforms S14 MH">Whitening and Coloring Transforms</a>, by <a href="User:Mhossain">Maliha Hossain</a>
 
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</li><li><a href="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 </a>, by Minwoong Kim (in Korean)  
*Slectures on Probability and Statistics  
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</li><li><a href="PCA">Principal Component Analysis (PCA)</a>, by <a href="http://web.ics.purdue.edu/~zhou338/">Tian Zhou</a>
**[[ECE662 Whitening and Coloring Transforms S14 MH|Whitening and Coloring Transforms]], by [[User:Mhossain|Maliha Hossain]]
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</li></ul>
**[[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)  
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</li><li>Slectures on Bayes Rule  
**[[PCA|Principal Component Analysis (PCA)]], by [http://web.ics.purdue.edu/~zhou338/ Tian Zhou]
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<ul><li><a href="From Bayes Theorem to Pattern Recognition via Bayes Rule">From Bayes' Theorem to Pattern Recognition via Bayes' Rule</a> by <a href="http://varunvasudevan.com/">Varun Vasudevan</a>
*Slectures on Bayes Rule  
+
</li><li><a href="Upper Bounds for Bayes Error">Upper Bounds for Bayes Error</a> by G. M. Dilshan Godaliyadda  
**[[From Bayes Theorem to Pattern Recognition via Bayes Rule|From Bayes' Theorem to Pattern Recognition via Bayes' Rule]] by [http://varunvasudevan.com/ Varun Vasudevan]
+
</li><li><a href="Test">Upper Bounds for Bayes Error (including the derivation of Chernoff Distance)</a> by Jeehyun Choe  
**[[Upper Bounds for Bayes Error|Upper Bounds for Bayes Error]] by G. M. Dilshan Godaliyadda  
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</li><li><a href="Slecture Bayes rule to minimize risk Andy Park ECE662 Spring 2014">Bayes Rule to minimize risk</a>, by Andy Park  
**[[Test|Upper Bounds for Bayes Error (including the derivation of Chernoff Distance)]] by Jeehyun Choe  
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</li><li><a href="Bayes Rule Minimize Risk Dennis Lee">Bayes Rule for Minimizing Risk</a> by Dennis Lee  
**[[Slecture Bayes rule to minimize risk Andy Park ECE662 Spring 2014|Bayes Rule to minimize risk]], by Andy Park  
+
</li><li>Link to slecture (use a descriptive title)  
**[[Bayes Rule Minimize Risk Dennis Lee|Bayes Rule for Minimizing Risk]] by Dennis Lee  
+
</li></ul>
**Link to slecture (use a descriptive title)  
+
</li><li>Slectures on Density Estimation  
*Slectures on Density Estimation  
+
<ul><li><a href="Mle tutorial">Tutorial on Maximum Likelihood Estimates</a> by Sudhir Kylasa  
**[[Mle tutorial|Tutorial on Maximum Likelihood Estimates]] by Sudhir Kylasa  
+
</li><li><a href="Introduction to local density estimation methods">Introduction to local (nonparametric) density estimation methods</a> by <a href="https://www.youtube.com/watch?v=WwPpsLjUsfQ">Yu Liu</a>
**[[Introduction_to_local_density_estimation_methods|Introduction to local (nonparametric) density estimation methods]] by Yu Liu  
+
</li></ul>
*Slectures on Linear Classifiers
+
</li><li>Slectures on Linear Classifiers
 
+
</li></ul>
----
+
<hr />
 
+
<h2> Peer Reviews </h2>
== Peer Reviews ==
+
<ul><li><a href="Instructions peer review hw1">Instruction for peer reviewing HW1</a>
 
+
</li><li>Heads up: peer review of hw2 will be due April 29
*[[Instructions peer review hw1|Instruction for peer reviewing HW1]]
+
</li></ul>
*Heads up: peer review of hw2 will be due April 29
+
<hr />
 
+
<h2> Discussion  </h2>
----
+
<p>Feel free to use the space below for discussion, or create a page for discussion and link it below.  
 
+
</p>
== Discussion  ==
+
<ul><li><a href="Data discussion HW1 ECE662 S14 Boutin">Where to find data for HW1</a>
 
+
</li><li><a href="Yelp Dataset">Possible Real-world data to use for class</a>
Feel free to use the space below for discussion, or create a page for discussion and link it below.  
+
</li><li><a href="Programming help ECE662S14">Programming help!</a>
 
+
</li><li>New Discussion
*[[Data discussion HW1 ECE662 S14 Boutin|Where to find data for HW1]]
+
</li></ul>
*[[Yelp Dataset|Possible Real-world data to use for class]]
+
<hr />
*[[Programming help ECE662S14|Programming help!]]
+
<p><a href="ECE662">Back to main ECE662 page</a>
*New Discussion
+
</p><a _fcknotitle="true" href="Category:ECE662Spring2014Boutin">ECE662Spring2014Boutin</a> <a _fcknotitle="true" href="Category:ECE">ECE</a> <a _fcknotitle="true" href="Category:ECE662">ECE662</a> <a _fcknotitle="true" href="Category:Pattern_recognition">Pattern_recognition</a>
 
+
----
+
 
+
[[ECE662|Back to main ECE662 page]]
+
 
+
[[Category:ECE662Spring2014Boutin]] [[Category:ECE]] [[Category:ECE662]] [[Category:Pattern_recognition]]
+

Revision as of 06:19, 16 April 2014



<a _fcknotitle="true" href="ECE662">ECE662</a>: 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:

  • <a href="User:Mboutin">Professor Mimi Boutin</a>
Office: MSEE342
<a href="Open office hours mboutin">Office hours</a>
<a href="https://www.projectrhea.org/rhea/index.php/Special:DropBox?forUser=mboutin&assn=true">Assignment Drop Box</a>

Lecture:

  • When? TuTh, 10:30 - 11:45
  • Where? EE117 (subject to change)

<a href="https://www.projectrhea.org/learning/slectures.php">Slectures</a>

Please use this <a href="Slecture template ECE662S14">template for text slectures</a> or this <a href="Slecture template video ECE662S14">template for video slectures</a>

  • Slectures on Probability and Statistics
    • <a href="ECE662 Whitening and Coloring Transforms S14 MH">Whitening and Coloring Transforms</a>, by <a href="User:Mhossain">Maliha Hossain</a>
    • <a href="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 </a>, by Minwoong Kim (in Korean)
    • <a href="PCA">Principal Component Analysis (PCA)</a>, by <a href="http://web.ics.purdue.edu/~zhou338/">Tian Zhou</a>
  • Slectures on Bayes Rule
    • <a href="From Bayes Theorem to Pattern Recognition via Bayes Rule">From Bayes' Theorem to Pattern Recognition via Bayes' Rule</a> by <a href="http://varunvasudevan.com/">Varun Vasudevan</a>
    • <a href="Upper Bounds for Bayes Error">Upper Bounds for Bayes Error</a> by G. M. Dilshan Godaliyadda
    • <a href="Test">Upper Bounds for Bayes Error (including the derivation of Chernoff Distance)</a> by Jeehyun Choe
    • <a href="Slecture Bayes rule to minimize risk Andy Park ECE662 Spring 2014">Bayes Rule to minimize risk</a>, by Andy Park
    • <a href="Bayes Rule Minimize Risk Dennis Lee">Bayes Rule for Minimizing Risk</a> by Dennis Lee
    • Link to slecture (use a descriptive title)
  • Slectures on Density Estimation
    • <a href="Mle tutorial">Tutorial on Maximum Likelihood Estimates</a> by Sudhir Kylasa
    • <a href="Introduction to local density estimation methods">Introduction to local (nonparametric) density estimation methods</a> by <a href="https://www.youtube.com/watch?v=WwPpsLjUsfQ">Yu Liu</a>
  • Slectures on Linear Classifiers

Peer Reviews

  • <a href="Instructions peer review hw1">Instruction for peer reviewing HW1</a>
  • 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.

  • <a href="Data discussion HW1 ECE662 S14 Boutin">Where to find data for HW1</a>
  • <a href="Yelp Dataset">Possible Real-world data to use for class</a>
  • <a href="Programming help ECE662S14">Programming help!</a>
  • New Discussion

<a href="ECE662">Back to main ECE662 page</a>

<a _fcknotitle="true" href="Category:ECE662Spring2014Boutin">ECE662Spring2014Boutin</a> <a _fcknotitle="true" href="Category:ECE">ECE</a> <a _fcknotitle="true" href="Category:ECE662">ECE662</a> <a _fcknotitle="true" href="Category:Pattern_recognition">Pattern_recognition</a>

Alumni Liaison

BSEE 2004, current Ph.D. student researching signal and image processing.

Landis Huffman