Lectures

 

Week Date Lecture Slides Readings Assignments
1 08/23 Introduction Han Ch 1  
2 08/28 Frequent Pattern Mining Han 6.1, 6.2 Hw1
2 08/30 Apriori help session (Farnaz)  
3 09/04 Labor day    
3 09/06 Frequent Pattern Mining    
4 09/11 Hurricane day 
4 09/13 Frequent Pattern Mining    
5 09/18 Clustering Han 10 Hw2
5 09/20 Clustering    
6 09/25 Clustering    
6 09/27 Clustering    
7 10/02 Similarity Search MMDS Ch 3
7 10/04 Similarity Search
8 10/09 Fall break
8 10/11 Similarity Search  
9 10/16 Ranking and Skyline Fagin '03 Reading Hw
9 10/18 Ranking and Skyline Bentley '80
Kossmann '02
 
10 10/23 Midterm (review, solution)  
10 10/25 Ranking and Skyline Papadias '03
Liu '15
Questionnaire
Hw3
11 10/30 PageRank MMDS Ch 5
11 11/01 Graphical Models Koller '07 Chapter  
12 11/06 Graphical Models    
12 11/08 Guest lecture: Truth inference using graphical models (Daniel Garcia Ulloa) Garcia '17  
13 11/13 Hidden Markov Models Jurafsky '17 Chapter  
13 11/15 Guest lecture: Modeling correlations for privacy preserving data mining using Markov Models and Markov Networks  (Yang Cao) Cao '17
Yang '15
 
14 11/20 Trajectory prediction using Markov models and pattern mining Zhou '13
Monreale '09
 
14 11/22 project day  
15 11/27 Project workshop: subspace and automatic clustering
- Exploring optimal subspace for k-means, Kenong Su, Yafet Kebede Amene, Ali Ahmadvand
- Evaluation of the sub k-means algorithm, Xiaofeng Shi, Lan Zhou, Ziyun Du
- Comparitive study of automatic *-means clustering algorithms, Lefei Chen, Lewie Wang
 
15 11/29 Project workshop: clustering, EM and skyline based classification
- Implementing and evaluating tx-means clustering, Eric Lee, Jueun Kim
- Evaluation of consensus clustering, Yidong Gong, Renjian Jiang, Yunchuan Kong
- Improving k-means to handle outliers, Zuowei Zhong, Ziwei Cheng
- Clustering based tensor decomposition, Huan He, Shihua Wang  Implementing
- EM Algorithm in Text Classification, Payam Karisani
- A novel classification method based on skyline queries, Jing Ma, Qiuchen Zhang
 
16 12/04 Project workshop: applications
- Kaggle: What's cooking? Qiyang Zhou, Rongmei Lin, Liquan Bai
- Kaggle: predicting check ins, Funing Chen, Siwei Wang
- Kaggle: product classification, Denis Whelan, Jin Ming
- Cluster analyasis on clinical data, Fereshteh Razmi, Azade Tabaie
- Using voice data to predict early-onset parkinson's disease, Reza Karimi, Derek Onken, Mani Sotoodeh