Interactive Clustering Barna Saha Clustering Learning over Noisy - PowerPoint PPT Presentation

Jun 23, 2023 •183 likes •322 views

Interactive Clustering Barna Saha Clustering Learning over Noisy Data Learn a classifier or find clusters over noisy/uncertain data Noise comes from using similarity func5onsadd an edge between two images if they represent the same

Interactive Clustering Barna Saha
Clustering
Learning over Noisy Data Learn a classifier or find clusters over noisy/uncertain data Noise comes from using similarity func5ons—add an edge between two images if they represent the same monument—clusters could be erroneous
Learning over Noisy Data Learn a classifier or find clusters over noisy/uncertain data Noise comes from inherent data errors/missing a?ributes—clustering collabora5on network • Learn a classifier or do clustering over noisy/uncertain data obtained from DBLP could be erroneous.
Further Applications • Linking Census Records • Public Health • Web search • Comparison shopping • Spam Detec5on • Machine Reading • IP Aliasing • ……..
Query complexity of optimal strategy?
Query complexity of optimal strategy? Davidson, Khanna, Milo, Roy, 2014
Faulty Oracle
Faulty Oracle Repeat the same ques5on. Assuming p=q, repeat each ques5on (say) 24log n/(1-2p) 2 5mes
Faulty Oracle
Faulty Oracle: No Resampling • Find seed nodes for each cluster • If we can find 24 log n/(1-2p) 2 seed nodes from each cluster then we are done! [Why?] ……………….. …..
Faulty Oracle: How to Cind seed nodes? • Let N=O(k 2 log n/(1-2p) 4 ) • Select N nodes and ask all possible pairwise queries among these nodes. • Run correla5on clustering algorithm in this small set of nodes • Each cluster returned by the correla5on clustering that has size at least 24 log n/(1-2p) 2 act as a seed
Faulty Oracle: How to Cind seed nodes? • Let N=O(k 2 log n/(1-2p) 4 ) • Select N nodes and ask all possible pairwise queries among these nodes. • Run correla5on clustering algorithm in this small set of nodes • Each cluster returned by the correla5on clustering that has size at least 24 log n/(1-2p) 2 act as a seed Some intui5on on the analysis: If we know all the query results, correla5on clustering gives the maximum likelihood es5mator. Moreover, it is an instance of correla5on clustering where errors are random— we know how to solve it!

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