CS Forum: Pauli Miettinen

Topic: Matrix factorization models for patterns beyond blocks

   Speaker: Pauli Miettinen

   Host: Prof. Aristides Gionis

   Time: 14:15-15:00 (coffee from 14:00)

   Venue: T2 in CS building, Konemiehentie 2

Matrix factorization models for patterns beyond blocks

Abstract

Finding patterns, or regularities, from data and using the patterns to summarise the data are in the core of data mining. In many cases, these patterns are "block-like": when the data can be expressed as a table of values, or as a matrix, the patterns are sub-tables (or sub-matrices) that are somehow different from the other parts of the data. Clustering, community detection, and frequent itemset mining can all be considered to find "block-like" patterns, to name a few examples. Block-like patters also fit well to the language of linear algebra, where we can model the block-like patterns as (approximate) rank-1 matrices, and data summarisations as matrix factorisations. Not all patterns or summaries in data mining are easy to express as matrix factorisations, though, and in recent years, patterns that go "beyond blocks" have become under active investigation. In this talk, I will discuss why being able to express the data mining task in matrix factorisation terms is important and cover my recent and ongoing work on different types of matrix factorisations that can be used to model patterns beyond blocks.

Bio

Pauli Miettinen did his PhD at University of Helsinki in Prof. Heikki Mannila's group, where he graduated at 2009. After a short post-doc period at Helsinki, he moved to Max Planck Institute for Informatics in Saarbrücken, Germany, where he is currently a senior researcher and the leader of research field Data Mining. His current research focus is on redescription mining and non-conventional matrix and tensor factorizations and their applications to data mining, in particular studying how we can generalize matrix and tensor factorization to model complex patterns and interactions. His work has appeared in numerous publications in top data mining and theoretical computer science venues. He has received two best paper awards and an honorary mention at 2010 ACM SIGKDD Doctoral dissertation awards. While he insists that 1+1=1, he accepts that other people might have different opinions.

The speaker will also be available for discussion Wednesday and Thursday. Please enquire of Aris Gionis aristides.gionis@aalto.fi to make arrangements.