Abstract:

It is widely accepted that machines can learn just like a normal human being does: feeding a learning algorithm with sufficient amount of training data, it can generate a model that maps the inputs to the most plausible outputs. Discovery, on the other hand, is about finding something for the first time, which has never been observed in the training data. One interesting question to ask is whether machines can perform discovery when there is no labelled data available. In this talk, I will introduce several of our recent findings in this direction, including identifying novel social links between users and items; finding missing correspondences between objects across domains using only rating data; inferring sensor values of unobserved locations; and deciphering the secret key in Cryptography, etc. Such findings show that with the availability of large unlabeled data and powerful computation infrastructure, machines can indeed perform discovery tasks.

Bio

Shou-de Lin is currently a full professor in the CSIE department of National Taiwan University. He holds a BS degree in EE department from National Taiwan University, an MS-EE degree from the University of Michigan, an MS degree in Computational Linguistics and PhD in Computer Science both from the University of Southern California. He leads the Machine Discovery and Social Network Mining Lab in NTU. Before joining NTU, he was a post-doctoral research fellow at the Los Alamos National Lab. Prof. Lin's research includes the areas of machine learning and data mining, social network analysis, and natural language processing. His international recognition includes the best paper award in IEEE Web Intelligent conference 2003, Google Research Award in 2007, Microsoft research award in 2008, 2015, 2016 merit paper award in TAAI 2010, 2014, 2016, best paper award in ASONAM 2011, US Aerospace AFOSR/AOARD research award winner for 5 years. He is the all-time winners in ACM KDD Cup, leading or co-leading the NTU team to win 5 championships. He also leads a team to win WSDM Cup 2016. He has served as the senior PC for SIGKDD and area chair for ACL. He is currently the associate editor for International Journal on Social Network Mining, Journal of Information Science and Engineering, and International Journal of Computational Linguistics and Chinese Language Processing. He is also a freelance writer for Scientific American.

All faculties and students are welcome to join.