m (removed "s" after http in slecture link) |
|||
| (13 intermediate revisions by the same user not shown) | |||
| Line 11: | Line 11: | ||
</font size> | </font size> | ||
| − | Multilingual [ | + | Multilingual [http://www.projectrhea.org/learning/slectures.php Slectures] by Students in the Spring 2014 Class of [[ECE662]] |
</center> | </center> | ||
---- | ---- | ||
| Line 19: | Line 19: | ||
**[[ECE662 Whitening and Coloring Transforms S14 MH|Text slecture in English]], by [[User:Mhossain|Maliha Hossain]] <span style="color:GREEN">Very clear!</span> | **[[ECE662 Whitening and Coloring Transforms S14 MH|Text slecture in English]], by [[User:Mhossain|Maliha Hossain]] <span style="color:GREEN">Very clear!</span> | ||
*How to generate random n dimensional data from two categories with different priors (use these methods to generate data for homework) | *How to generate random n dimensional data from two categories with different priors (use these methods to generate data for homework) | ||
| − | **[[Generating random data with controlled prior probabilities slecture ECE662S14 Gheith|Video slecture in English]] by Alex Gheith | + | **[[Generating random data with controlled prior probabilities slecture ECE662S14 Gheith|Video slecture in English]] by Alex Gheith <span style="color:GREEN">Newbies can start here</span> |
| − | **[[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 | + | **[[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">Newbies can start here- if they speak Korean</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 | + | **[[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">Newbies can start here- if you they speak Korean</span> |
| − | **[[The principles for how to generate random samples from a Gaussian distribution|Text slecture in English]] by Joonsoo Kim | + | **[[The principles for how to generate random samples from a Gaussian distribution|Text slecture in English]] by Joonsoo Kim <span style="color:GREEN">More Advanced</span> |
| − | **[[Generation of N-dimensional normally distributed random numbers from two categories with different priors|Text slecture in English]] by Jonghoon Jin | + | **[[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">More Advanced</span> |
*Principal Component Analysis (PCA) | *Principal Component Analysis (PCA) | ||
| − | **[[PCA|Text slecture in English]], by [http://web.ics.purdue.edu/~zhou338/ Tian Zhou] | + | **[[PCA|Text slecture in English]], by [http://web.ics.purdue.edu/~zhou338/ Tian Zhou] <span style="color:GREEN">Starts very slowly.</span> |
| − | **[[PCA Theory Examples|Text slecture in English]], by Sujin Jang | + | **[[PCA Theory Examples|Text slecture in English]], by Sujin Jang <span style="color:GREEN">Jumps right into linear algebra at the beginning.</span> |
| − | **[[ | + | **[[Pca khalid|Video slecture in English]], by Khalid Tahboub <span style="color:GREEN">Clearly explains why it's not good when trying to recognize patterns</span> |
| − | **[[ | + | **[[Kernel PCA|Video slecture in English, and Chinese]], by Tsung Tai Yeh <span style="color:GREEN">More Advanced. Covers kernel PCA.</span> |
*The Curse of Dimensionality | *The Curse of Dimensionality | ||
| − | **[[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 <span style="color:GREEN">Text flows nicely. Fun read.</span> |
==2. Bayes Rule == | ==2. Bayes Rule == | ||
| − | + | *Bayes Rule in Layman's Terms | |
| − | + | **[[Introduction to Bayes' Rule|Video slecture in Spanish]] by Francis Phillip | |
| − | + | *Derivation of Bayes Rule | |
| − | + | **[[Derivation of Bayes rule Anonymous7|Text slecture in English]] By Anonymous7 | |
| − | + | **[[From Bayes Theorem to Pattern Recognition via Bayes Rule|Text slecture in English]] by [http://varunvasudevan.com/ Varun Vasudevan] | |
| − | + | **[[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 of Bayes rule In Greek|Text slecture in Greek]] by Stylianos Chatzidakis | |
| − | + | **[[Derivation of Bayes rule In Chinese|Text slecture in Chinese]] by Weibao Wang | |
| − | + | *Optimality of Bayes Rule | |
| − | + | **[[Slecture optimality bayes decision rule michaux ECE662S14|Video slecture in English]] by Aaron Michaux | |
| − | + | **[[Kjw810313|Video slecture in Korean]] by Jeong-wan Kim | |
| − | + | *Upper Bounds for Bayes Error | |
| − | + | **[[Upper Bounds for Bayes Error|Text slecture in English]] by G. M. Dilshan Godaliyadda | |
| − | + | **[[Test|Text slecture in English (includes the derivation of Chernoff Distance)]] by Jeehyun Choe | |
| − | + | *Bayes Rule to Minimize Risk | |
| − | + | **[[Slecture Bayes rule to minimize risk Andy Park ECE662 Spring 2014|Video slectures in English]], by Andy Park | |
| − | + | **[[Ness slecture 2014|Text slecture in Chinese]] by Robert Ness | |
| − | + | **[[Bayes Rule Minimize Risk Dennis Lee|Text slecture in English]] by Dennis Lee | |
| − | + | *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 | |
| − | + | *Bayes rule in practice | |
| − | + | **[[Bayes rule in practice|Text slecture in English]] by Lu Wang | |
| − | + | **[[662slecture tang|Text slecture in English]] by Chuohao Tang | |
| − | + | *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] | **[[Neyman-Pearson Lemma and Receiver Operating Characteristic Curve|Text slecture in English]] by [https://engineering.purdue.edu/~lee714/ Soonam Lee] | ||
**[[ROC curve analysis slecture ECE662 Spring0214 Sun|Video slecture in English]] by Jianxin Sun | **[[ROC curve analysis slecture ECE662 Spring0214 Sun|Video slecture in English]] by Jianxin Sun | ||
| Line 64: | Line 63: | ||
==3. Global (parametric) Density Estimation Methods== | ==3. Global (parametric) Density Estimation Methods== | ||
*Maximum Likelihood Estimation (MLE) | *Maximum Likelihood Estimation (MLE) | ||
| − | **[[Mle tutorial|Text slecture in English]] by Sudhir Kylasa | + | **[[Mle tutorial|Text slecture in English]] by Sudhir Kylasa |
**[[Maximum Likelihood Estimation Analysis for various Probability Distributions|Text slecture in English]] by Hariharan Seshadri | **[[Maximum Likelihood Estimation Analysis for various Probability Distributions|Text slecture in English]] by Hariharan Seshadri | ||
**[[Video slecture in English: Introduction to Maximum Likelihood Estimation|Video slecture in English]] by Anantha Raghuraman | **[[Video slecture in English: Introduction to Maximum Likelihood Estimation|Video slecture in English]] by Anantha Raghuraman | ||
Latest revision as of 10:38, 22 January 2015
The Boutin Lectures on Statistical Pattern Recognition
Multilingual Slectures by Students in the Spring 2014 Class of ECE662
Contents
0. Foreword by Professor Boutin
1. Background Material
- Whitening and Coloring Transforms
- Text slecture in English, by Maliha Hossain Very clear!
- How to generate random n dimensional data from two categories with different priors (use these methods to generate data for homework)
- Video slecture in English by Alex Gheith Newbies can start here
- Video slecture in Korean , by Minwoong Kim Newbies can start here- if they speak Korean
- Video slecture in Korean , by Hyun Dok Cho Newbies can start here- if you they speak Korean
- Text slecture in English by Joonsoo Kim More Advanced
- Text slecture in English by Jonghoon Jin More Advanced
- Principal Component Analysis (PCA)
- Text slecture in English, by Tian Zhou Starts very slowly.
- Text slecture in English, by Sujin Jang Jumps right into linear algebra at the beginning.
- Video slecture in English, by Khalid Tahboub Clearly explains why it's not good when trying to recognize patterns
- Video slecture in English, and Chinese, by Tsung Tai Yeh More Advanced. Covers kernel PCA.
- The Curse of Dimensionality
- Text slecture in English, and in Chinese by Haonan Yu Text flows nicely. Fun read.
2. Bayes Rule
- Bayes Rule in Layman's Terms
- Video slecture in Spanish by Francis Phillip
- Derivation of Bayes Rule
- Text slecture in English By Anonymous7
- Text slecture in English by Varun Vasudevan
- Video slecture in English by Nadra Guizani
- Video slecture in English by Jieun Kim
- Text slecture in Greek by Stylianos Chatzidakis
- Text slecture in Chinese by Weibao Wang
- Optimality of Bayes Rule
- Video slecture in English by Aaron Michaux
- Video slecture in Korean by Jeong-wan Kim
- Upper Bounds for Bayes Error
- Text slecture in English by G. M. Dilshan Godaliyadda
- Text slecture in English (includes the derivation of Chernoff Distance) by Jeehyun Choe
- Bayes Rule to Minimize Risk
- Video slectures in English, by Andy Park
- Text slecture in Chinese by Robert Ness
- Text slecture in English by Dennis Lee
- Bayes Rule for Normally Distributed Features
- Text slecture in English by Yanzhe Cui
- Text slecture in English by Jihwan Lee
- Bayes rule in practice
- Text slecture in English by Lu Wang
- Text slecture in English by Chuohao Tang
- Neyman-Pearson test and ROC curves
- Text slecture in English by Soonam Lee
- Video slecture in English by Jianxin Sun
- Text slecture in English by Hao Lin
3. Global (parametric) Density Estimation Methods
- Maximum Likelihood Estimation (MLE)
- Text slecture in English by Sudhir Kylasa
- Text slecture in English by Hariharan Seshadri
- Video slecture in English by Anantha Raghuraman
- Video slecture in English by Spencer Carver
- Text slecture in English by Lu Zhang
- Video slecture in English by Keehwan Park
- Text slecture in English by Wen Yi
- Text slecture in English by Zhenpeng Zhao
- Bayesian Estimation (BPE)
- Text slecture in English by Haiguang Wen
- Text slecture in English, by Shaobo Fang
- Text slecture in English by Yu Wang
4. Local ("non-parametric") Density Estimation Methods
- Introduction to Local density Estimation Techniques (so-called "non-parametric")
- Text slecture in English by Yu Liu
- Video slecture in Russian by Aziza Satkhozhina
- Video slecture in English by Nusaybah Abu-Mulaweh
- Video slecture in English by Chenxi Yuan
- Density Estimation with Parzen Windows
- Text slecture in English by Chiho Choi
- Text slecture in English by Ben Foster
- Text slecture in English by Abdullah Alshaibani
- Density Estimation with K-Nearest Neighbors (KNN)
- Text slecture in English by Raj Praveen Selvaraj
- Text slecture in English by Dan Barrett
- Video slecture in English by Qi Wang
- The Nearest Neighbor Decision Rule
- Text slecture in English by Sang Ho Yoon
- Text slecture in English by Jonathan Manring
5. Linear Classifiers
- Linear classifiers, projective coordinates, and Fisher linear discriminant
- Text slecture in English by John Mulcahy-Stanislawczyk
- Text slecture in English by Borui Chen
- Support Vector Machines (SVM)
- Text slecture in English by Xing Liu
- Video slecture in English by Tao Jiang
6. Supplementary Material
- Clustering Algorithms
- text slecture in English by David Runyan
Go to ECE662 Spring 2014 Course Wiki
Go to Slecture Page
