Machine Learning Coffee seminar "Scalable Algorithms for Extreme Multi-Class and Multi-Label Classificiation in Big Data"

Lecturer : 
Rohit Babbar
Event type: 
HIIT seminar
Doctoral dissertation
Event time: 
2018-01-15 09:15 to 10:00
Lecture room T2, CS building, Konemiehentie 2, Otaniemi

Rohit Babbar, Professor of Computer Science, Aalto University

Scalable Algorithms for Extreme Multi-Class and Multi-Lable Classification in Big Data

Abstract: In the era of big data, large-scale classification involving tens of thousand target categories is not uncommon. Also referred to as Extreme Classification, it has also been recently shown that the machine learning challenges arising in ranking, recommendation systems and web-advertising can be effectively addressed by reducing it to extreme multi-label classification framework. In this talk, I will discuss my two recent works, and present TerseSVM and DiSMEC algorithms for extreme multi-class and multi-label classification. The precision@k and nDCG@k results using DiSMEC improve by upto 20% on benchmark datasets over state-of-the-art methods, which are used by Microsoft in production system of Bing Search. The training process for these algorithms makes use of openMP based distributed architectures, and is able to leverage thousands of cores for computation.

Machine Learning Coffee seminars are weekly seminars held jointly by the Aalto University and the University of Helsinki. The seminars aim to gather people from different fields of science with interest in machine learning. Talks will begin at 9:15 am and porridge and coffee will be served from 9:00 am.

Next talk:

January 22, Kumpula: Mikko Koivisto



Last updated on 12 Jan 2018 by Homayun Afrabandpey - Page created on 12 Jan 2018 by Homayun Afrabandpey