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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">
 
== &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; '''Welcome to ECE662!'''  ==
 
== &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; '''Welcome to ECE662!'''  ==
 
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* The cleaned up version of the slectures is [[2014_Spring_ECE_662_Boutin_Statistical_Pattern_recognition_slectures|here]].  
*HW2 grades have been entered into the "instructor's Comment" box.  
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*Reviews for HW2 are activated. Please complete your review before class on Tuesday April 29.
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*Does anybody in the class speak Spanish (besides Francis)? If so, please send me an email. -pm
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*Does anybody in the class speak Russian (besides Aziza)? If so, please send me an email. -pm
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</div>  
 
</div>  
 
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== [https://www.projectrhea.org/learning/slectures.php Slectures]  ==
 
== [https://www.projectrhea.org/learning/slectures.php Slectures]  ==
 +
The cleaned up version of these slectures is [[2014_Spring_ECE_662_Boutin_Statistical_Pattern_recognition_slectures|HERE]]
  
 
Please use this [[Slecture template ECE662S14|template for text slectures]] or this [[Slecture template video ECE662S14|template for video slectures]]  
 
Please use this [[Slecture template ECE662S14|template for text slectures]] or this [[Slecture template video ECE662S14|template for video slectures]]  
  
 
*Slectures on Probability and Statistics  
 
*Slectures on Probability and Statistics  
**[[ECE662 Whitening and Coloring Transforms S14 MH|Whitening and Coloring Transforms]], by [[User:Mhossain|Maliha Hossain]]  
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**[[ECE662 Whitening and Coloring Transforms S14 MH|Whitening and Coloring Transforms]], by [[User:Mhossain|Maliha Hossain]] <span style="color:GREEN">OK</span>
**[[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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**How to generate random n dimensional data from two categories with different priors
**[[PCA|Principal Component Analysis (PCA)]], by [http://web.ics.purdue.edu/~zhou338/ Tian Zhou]  
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***[[Generating random data with controlled prior probabilities slecture ECE662S14 Gheith|Video slecture in English]] by Alex Gheith <span style="color:GREEN">OK</span>
**[[PCA_Theory_Examples|Basics & Examples of PCA]], by Sujin Jang
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***[[How to generate random n dimensional data from two categories with different priors slecture Minwoong Kim ECE662 Spring 2014|Video slecture in Korean ]], by Minwoong Kim <span style="color:GREEN">OK</span>
 +
***[[How to generate random n dimensional data from two categories with different priors slecture Minwoong Cho ECE662 Spring 2014|Video slecture in Korean ]], by Hyun Dok Cho <span style="color:GREEN">OK</span>
 +
***[[The principles for how to generate random samples from a Gaussian distribution|Text slecture in English]] by Joonsoo Kim <span style="color:GREEN">OK</span>
 +
***[[Generation of N-dimensional normally distributed random numbers from two categories with different priors|Text slecture in English]] by Jonghoon Jin <span style="color:GREEN">OK</span>
 +
**Principal Component Analysis (PCA)  
 +
***[[PCA|Text slecture in English]], by [http://web.ics.purdue.edu/~zhou338/ Tian Zhou] <span style="color:GREEN">OK</span>
 +
***[[PCA Theory Examples|Text slecture in English]], by Sujin Jang <span style="color:GREEN">OK</span>
 +
***[[Kernel PCA|Video slecture in English, and Chinese]], by Tsung Tai Yeh <span style="color:GREEN">OK</span>
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***[[Pca khalid|Video slecture in English]], by Khalid Tahboub <span style="color:GREEN" />
 
*Slectures on Curse of Dimensionality  
 
*Slectures on Curse of Dimensionality  
**[[Curse of Dimensionality|Text slecture in English]], and [[Curse of Dimensionality Chinese|in Chinese]] by Haonan Yu  
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**[[Curse of Dimensionality|Text slecture in English]], and [[Curse of Dimensionality Chinese|in Chinese]] by Haonan Yu USE SAME COMMENT PAGE FOR BOTH ENGLISH AND CHINESE VERSION
 
*Slectures on Bayes Rule  
 
*Slectures on Bayes Rule  
 
**Bayes Rule in Layman's Terms  
 
**Bayes Rule in Layman's Terms  
***Link to page here
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***[[Introduction to Bayes' Rule|Video slecture in Spanish]] by Francis Phillip <span style="color:GREEN">OK</span>
 
**Derivation of Bayes Rule  
 
**Derivation of Bayes Rule  
***[[From Bayes Theorem to Pattern Recognition via Bayes Rule|Text slecture in English]] by [http://varunvasudevan.com/ Varun Vasudevan]<br>  
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***[[Derivation of Bayes rule Anonymous7|Text slecture in English]] By Anonymous7 <span style="color:GREEN">OK</span>
***[[Derivation of Bayes' Rule from Bayes' Theorem|Video slecture in English]] by Nadra Guizani  
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***[[From Bayes Theorem to Pattern Recognition via Bayes Rule|Text slecture in English]] by [http://varunvasudevan.com/ Varun Vasudevan] <span style="color:GREEN">OK</span>  
***[[Derivation Bayes Rule slecture ECE662 Spring2014 Kim|Video slecture in English]] by Jieun Kim  
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***[[Derivation of Bayes' Rule from Bayes' Theorem|Video slecture in English]] by Nadra Guizani <span style="color:GREEN">OK</span>
***[[Derivation of Bayes rule In Greek|Text slecture in Greek]] by Stylianos Chatzidakis  
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***[[Derivation Bayes Rule slecture ECE662 Spring2014 Kim|Video slecture in English]] by Jieun Kim <span style="color:GREEN">OK</span>
**Bayes Rule for Normally distributed Features
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***[[Derivation of Bayes rule In Greek|Text slecture in Greek]] by Stylianos Chatzidakis <span style="color:GREEN">OK</span>
***[[Bayes Rule for 1-dimensional and N-dimensional feature spaces|Text slecture in English]] by Jihwan Lee
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***[[Derivation of Bayes rule In Chinese|Text slecture in Chinese]] by Weibao Wang <span style="color:GREEN">OK</span>
 +
**Optimality of Bayes Rule  
 +
***[[Slecture optimality bayes decision rule michaux ECE662S14|Video slecture in English]] by Aaron Michaux <span style="color:GREEN">OK</span>
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***[[Kjw810313|Video slecture in Korean]] by Jeong-wan Kim <span style="color:GREEN">OK</span>
 
**Upper Bounds for Bayes Error  
 
**Upper Bounds for Bayes Error  
***[[Upper Bounds for Bayes Error|Text slecture in English]] by G. M. Dilshan Godaliyadda  
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***[[Upper Bounds for Bayes Error|Text slecture in English]] by G. M. Dilshan Godaliyadda
***[[Upper Bound for Bayes error|Text slecture in English]] by Yihan Ding PLEASE FOLLOW TEMPLATE
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***[[Test|Text slecture in English (includes the derivation of Chernoff Distance)]] by Jeehyun Choe <span style="color:GREEN">OK</span>
***[[Test|Text slecture in English (includes the derivation of Chernoff Distance)]] by Jeehyun Choe  
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**Bayes Rule to Minimize Risk  
 
**Bayes Rule to Minimize Risk  
***[[Slecture Bayes rule to minimize risk Andy Park ECE662 Spring 2014|Video slectures in English]], by Andy Park  
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***[[Slecture Bayes rule to minimize risk Andy Park ECE662 Spring 2014|Video slectures in English]], by Andy Park <span style="color:GREEN">OK</span>
***[[Bayes Rule Minimize Risk Dennis Lee|Text slecture in English]] by Dennis Lee  
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***[[Ness slecture 2014|Text slecture in Chinese]] by Robert Ness <span style="color:GREEN">OK</span>
**[[Bayes rule in practice]] by Lu Wang  
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***[[Bayes Rule Minimize Risk Dennis Lee|Text slecture in English]] by Dennis Lee <span style="color:GREEN">OK</span>
 +
**Bayes Rule for Normally Distributed Features
 +
***[[Discussion about Discriminant Functions for the Multivariate Normal Density|Text slecture in English]] by Yanzhe Cui
 +
***[[Bayes Rule for 1-dimensional and N-dimensional feature spaces|Text slecture in English]] by Jihwan Lee <span style="color:GREEN">OK</span>
 +
**Bayes rule in practice  
 +
***[[Bayes rule in practice|Text slecture in English]] by Lu Wang <span style="color:GREEN">OK</span>
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***[[662slecture tang|Text slecture in English]] by Chuohao Tang <span style="color:GREEN">OK</span>
 
*Slectures on Neyman-Pearson test and ROC curves  
 
*Slectures on Neyman-Pearson test and ROC curves  
**[[Neyman-Pearson_Lemma_and_Receiver_Operating_Characteristic_Curve|Text slecture in English]] by [https://engineering.purdue.edu/~lee714/ Soonam Lee]  
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**[[Neyman-Pearson Lemma and Receiver Operating Characteristic Curve|Text slecture in English]] by [https://engineering.purdue.edu/~lee714/ Soonam Lee] <span style="color:GREEN">OK</span>
**[[ROC_curve_analysis_slecture_ECE662_Spring0214_Sun|ROC Curve and Analysis]] by Jianxin Sun
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**[[ROC curve analysis slecture ECE662 Spring0214 Sun|Video slecture in English]] by Jianxin Sun <span style="color:GREEN">OK</span>
 
*Slectures on Density Estimation  
 
*Slectures on Density Estimation  
 
**Maximum Likelihood Estimation (MLE)  
 
**Maximum Likelihood Estimation (MLE)  
***[[Mle tutorial|Text slecture in English]] by Sudhir Kylasa  
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***[[Mle tutorial|Text slecture in English]] by Sudhir Kylasa <span style="color:GREEN">OK</span>
***[[Maximum Likelihood Estimation Analysis for various Probability Distributions|Text slecture in English]] by Hariharan Seshadri  
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***[[Maximum Likelihood Estimation Analysis for various Probability Distributions|Text slecture in English]] by Hariharan Seshadri <span style="color:GREEN">OK</span>
***[[Expected Value and Deviation of Maximum LIkelihood Estimates over Multiple Trials]] by Spencer Carver  
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***[[Video slecture in English: Introduction to Maximum Likelihood Estimation|Video slecture in English]] by Anantha Raghuraman <span style="color:GREEN">OK</span>
***[[Deviation of Maximum Likelihood Estimators and Basic Properties of ML Method|Text slecture in English]] by Lu Zhang  
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***[[Convergence of the Maximum Likelihood Estimator over Multiple Trials|Video slecture in English]] by [http://web.ics.purdue.edu/~scarver/ Spencer Carver] <span style="color:GREEN">OK</span>
***[[Introduction to Maximum likelihood estimate]] by Anantha Raghuraman
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***[[Maximum Likelihood Estimators and Examples|Text slecture in English]] by Lu Zhang <span style="color:GREEN">OK</span>
 +
***[[SlectureKeehwanECE662Spring14|Video slecture in English]] by Keehwan Park <span style="color:GREEN">OK</span>
 +
***[[MLEforGMM|Text slecture in English]] by Wen Yi
 +
***[[ECE662Selecture zhenpengMLE|Text slecture in English]] by Zhenpeng Zhao
 
**Bayesian Estimation (BPE)  
 
**Bayesian Estimation (BPE)  
***[[Bayes_Parameter_Estimation|Text slecture in English]] by Haiguang Wen  
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***[[Bayes Parameter Estimation|Text slecture in English]] by Haiguang Wen <span style="color:GREEN">OK</span>
 
***[[Bayersian Parameter Estimation: Gaussian Case|Text slecture in English]], by Shaobo Fang  
 
***[[Bayersian Parameter Estimation: Gaussian Case|Text slecture in English]], by Shaobo Fang  
 +
***[[Bayes Parameter Estimation with examples|Text slecture in English]] by Yu Wang 
 
**Introduction to Local density Estimation Techniques (so-called "non-parametric")  
 
**Introduction to Local density Estimation Techniques (so-called "non-parametric")  
***[[Introduction to local density estimation methods|Text slecture in English]] by Yu Liu  
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***[[Introduction to local density estimation methods|Text slecture in English]] by Yu Liu <span style="color:GREEN">OK</span>
***[[Slecture_Introduction_local_density_estimation_methods_ECE662_Spring2014_Aziza|Video slecture in Russian]] by Aziza Satkhozhina
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***[[Slecture Introduction local density estimation methods ECE662 Spring2014 Aziza|Video slecture in Russian]] by Aziza Satkhozhina  
 +
***[[Introduction to local density estimation methods ECE662 Spring2014 Nusaybah|Video slecture in English]] by Nusaybah Abu-Mulaweh
 +
***[[Intro local non parametric density estimation methods ECE662 Spring2014 Yuan|Video slecture in English]] by Chenxi Yuan <span style="color:GREEN">OK</span>
 
**Density Estimation with Parzen Windows  
 
**Density Estimation with Parzen Windows  
***[[ParzenWindow|Parzen Window method for classification - Text slecture in English]] by Chiho Choi
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***[[ParzenWindow|Text slecture in English]] by Chiho Choi <span style="color:GREEN">OK</span>
***[[Parzen Window Density Estimation]] by Ben Foster  
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***[[Parzen Window Density Estimation|Text slecture in English]] by Ben Foster <span style="color:GREEN">OK</span>
***Link here
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***[[Parzen Windows|Text slecture in English]] by Abdullah Alshaibani <span style="color:GREEN">OK</span>
 
**Density Estimation with K-Nearest Neighbors (KNN)  
 
**Density Estimation with K-Nearest Neighbors (KNN)  
***Link here
+
***[[KnnDensityEstimation|Text slecture in English]] by Raj Praveen Selvaraj <span style="color:GREEN">OK</span>
 +
***[[Knearestneighbors|Text slecture in English]] by Dan Barrett QUESTION PAGE
 +
***[[K-Nearest Neighbors Density Estimation|Video slecture in English]] by Qi Wang <span style="color:GREEN">OK</span>
 
**The Nearest Neighbor Decision Rule  
 
**The Nearest Neighbor Decision Rule  
***[[Estimation Using Nearest Neighbor|Text slecture in English]] by Sang Ho Yoon  
+
***[[Estimation Using Nearest Neighbor|Text slecture in English]] by Sang Ho Yoon
*Slectures on Linear Classifiers
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***[[Slecture from KNN to nearest neighbor|Text slecture in English]] by Jonathan Manring <span style="color:GREEN">OK</span>
**[[Solving Linear Regression Problems using Support Vector Machine ]] by Xing Liu  
+
*Slectures on Linear Classifiers  
 +
**[[JMSLinearClassifierSlecture|Text slecture in English]] by John Mulcahy-Stanislawczyk
 +
**[[CBR_logistic_regression|Text slecture in English]] by Borui Chen
 +
*Slectures on Support Vector Machines (SVM)
 +
**[https://kiwi.ecn.purdue.edu/rhea/index.php/Least_Squares_Support_Vector_Machine_and_its_Applications_in_Solving_Linear_Regression_Problems Text slecture in English] by Xing Liu  
 +
**[[Support Vector Machine|Video slecture in English]] by Tao Jiang
 +
*Slectures on Clustering Algorithms (supplemental material)
 +
**[[SlectureDavidRunyanCS662Spring14|text slecture in English]] by David Runyan
 +
 
 
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Latest revision as of 19:50, 2 May 2016



ECE662: Statistical Pattern Recognition and Decision Making Processes, Spring 2014 (cross-listed with CS662)


                Welcome to ECE662!

  • The cleaned up version of the slectures is here.

Course Information

Instructor:

Office: MSEE342
Office hours
Assignment Drop Box

Lecture:

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

Slectures

The cleaned up version of these slectures is HERE

Please use this template for text slectures or this template for video slectures


Peer Reviews


Discussion

Feel free to use the space below for discussion, or create a page for discussion and link it below.


Back to main ECE662 page

Alumni Liaison

Abstract algebra continues the conceptual developments of linear algebra, on an even grander scale.

Dr. Paul Garrett