| Line 8: | Line 8: | ||
<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!''' == | ||
| + | |||
*HW2 grades have been entered into the "instructor's Comment" box. | *HW2 grades have been entered into the "instructor's Comment" box. | ||
*Reviews for HW2 are activated. Please complete your review before class on Tuesday April 29. | *Reviews for HW2 are activated. Please complete your review before class on Tuesday April 29. | ||
| Line 43: | Line 44: | ||
**[[Curse of Dimensionality|Text slecture in English]], and [[Curse of Dimensionality Chinese|in Chinese]] by Haonan Yu | **[[Curse of Dimensionality|Text slecture in English]], and [[Curse of Dimensionality Chinese|in Chinese]] by Haonan Yu | ||
*Slectures on Bayes Rule | *Slectures on Bayes Rule | ||
| − | **Bayes Rule in Layman's Terms | + | **Bayes Rule in Layman's Terms |
| − | ***Link to page here | + | ***Link to page here |
**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> | + | ***[[From Bayes Theorem to Pattern Recognition via Bayes Rule|Text slecture in English]] by [http://varunvasudevan.com/ Varun Vasudevan]<br> |
***[[Derivation of Bayes' Rule from Bayes' Theorem|Video slecture in English]] by Nadra Guizani | ***[[Derivation of Bayes' Rule from Bayes' Theorem|Video slecture in English]] by Nadra Guizani | ||
***[[Derivation Bayes Rule slecture ECE662 Spring2014 Kim|Video slecture in English]] by Jieun Kim | ***[[Derivation Bayes Rule slecture ECE662 Spring2014 Kim|Video slecture in English]] by Jieun Kim | ||
| − | ***[[Derivation of Bayes | + | ***[[Derivation of Bayes rule In Greek]] by Stylianos Chatzidakis |
| − | **Bayes Rule for Normally distributed Features | + | **Bayes Rule for Normally distributed Features |
| − | ***[[ | + | ***[[Bayes Rule for 1-dimensional and N-dimensional feature spaces|Text slecture in English]] by Jihwan Lee |
**Upper Bounds for Bayes Error | **Upper Bounds for Bayes Error | ||
***[[Upper Bounds for Bayes Error|Text slecture in English]] by G. M. Dilshan Godaliyadda | ***[[Upper Bounds for Bayes Error|Text slecture in English]] by G. M. Dilshan Godaliyadda | ||
| Line 61: | Line 62: | ||
**[[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 | ||
| − | **[[Neyman-Pearson Lemma and Receiver Operating Characteristic Curve]] by [https://engineering.purdue.edu/~lee714/ Soonam Lee] | + | **[[Neyman-Pearson Lemma and Receiver Operating Characteristic Curve]] by [https://engineering.purdue.edu/~lee714/ Soonam Lee] |
*Slectures on Density Estimation | *Slectures on Density Estimation | ||
**Maximum Likelihood Estimation (MLE) | **Maximum Likelihood Estimation (MLE) | ||
***[[Mle tutorial|Tutorial on Maximum Likelihood Estimates]] by Sudhir Kylasa | ***[[Mle tutorial|Tutorial on Maximum Likelihood Estimates]] by Sudhir Kylasa | ||
| − | ***[[Maximum Likelihood Estimation Analysis for various Probability Distributions]] by Hariharan Seshadri | + | ***[[Maximum Likelihood Estimation Analysis for various Probability Distributions]] by Hariharan Seshadri |
| − | ***[[Expected Value and Deviation of Maximum LIkelihood Estimates over Multiple Trials]] by Spencer Carver | + | ***[[Expected Value and Deviation of Maximum LIkelihood Estimates over Multiple Trials]] by Spencer Carver |
| − | ***[[Deviation of Maximum Likelihood Estimators and Basic Properties of ML Method]] by Lu Zhang | + | ***[[Deviation of Maximum Likelihood Estimators and Basic Properties of ML Method]] by Lu Zhang |
| − | ***[[Introduction to Maximum likelihood estimate]] by Anantha Raghuraman | + | ***[[Introduction to Maximum likelihood estimate]] by Anantha Raghuraman |
**Bayesian Estimation (BPE) | **Bayesian Estimation (BPE) | ||
| − | *** | + | ***[https://kiwi.ecn.purdue.edu/rhea/index.php/Bayes_Parameter_Estimation Bayes Parameter Estimation (BPE) tutorial] by Haiguang Wen<br> |
**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|Introduction to local (nonparametric) density estimation methods]] by [https://www.youtube.com/watch?v=WwPpsLjUsfQ Yu Liu] | ***[[Introduction to local density estimation methods|Introduction to local (nonparametric) density estimation methods]] by [https://www.youtube.com/watch?v=WwPpsLjUsfQ Yu Liu] | ||
**Density Estimation with Parzen Windows | **Density Estimation with Parzen Windows | ||
| − | ***[[ParzenWindow|Parzen window method with cubic window - Text slecture in English]] by Chiho Choi | + | ***[[ParzenWindow|Parzen window method with cubic window - Text slecture in English]] by Chiho Choi |
***Link here | ***Link here | ||
**Density Estimation with K-Nearest Neighbors (KNN) | **Density Estimation with K-Nearest Neighbors (KNN) | ||
***Link here | ***Link here | ||
**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 | *Slectures on Linear Classifiers | ||
Revision as of 07:45, 29 April 2014
Contents
ECE662: Statistical Pattern Recognition and Decision Making Processes, Spring 2014 (cross-listed with CS662)
Welcome to ECE662!
- HW2 grades have been entered into the "instructor's Comment" box.
- 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
- Slectures on Curse of Dimensionality
- Text slecture in English, and in Chinese by Haonan Yu
- Slectures on Bayes Rule
- Bayes Rule in Layman's Terms
- Link to page here
- Derivation of Bayes Rule
- Text slecture in English by Varun Vasudevan
- Video slecture in English by Nadra Guizani
- Video slecture in English by Jieun Kim
- Derivation of Bayes rule In Greek by Stylianos Chatzidakis
- Text slecture in English by Varun Vasudevan
- Bayes Rule for Normally distributed Features
- Text slecture in English by Jihwan Lee
- Upper Bounds for Bayes Error
- Text slecture in English by G. M. Dilshan Godaliyadda
- Text slecture in English by Yihan Ding PLEASE FOLLOW TEMPLATE
- 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
- Bayes Rule in Layman's Terms
- Slectures on Neyman-Pearson test and ROC curves
- Slectures on Density Estimation
- Maximum Likelihood Estimation (MLE)
- Tutorial on Maximum Likelihood Estimates by Sudhir Kylasa
- Maximum Likelihood Estimation Analysis for various Probability Distributions by Hariharan Seshadri
- Expected Value and Deviation of Maximum LIkelihood Estimates over Multiple Trials by Spencer Carver
- Deviation of Maximum Likelihood Estimators and Basic Properties of ML Method by Lu Zhang
- Introduction to Maximum likelihood estimate by Anantha Raghuraman
- Bayesian Estimation (BPE)
- Bayes Parameter Estimation (BPE) tutorial by Haiguang Wen
- Bayes Parameter Estimation (BPE) tutorial by Haiguang Wen
- Introduction to Local density Estimation Techniques (so-called "non-parametric")
- Density Estimation with Parzen Windows
- Parzen window method with cubic window - Text slecture in English by Chiho Choi
- Link here
- Density Estimation with K-Nearest Neighbors (KNN)
- Link here
- The Nearest Neighbor Decision Rule
- Text slecture in English by Sang Ho Yoon
- 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
