Title: Pricing Information and Validating Network Classifiers

Speaker: Eric Bax, Yahoo!

Abstract:

Pricing Information: In auctions for online advertising, data providers tell advertisers which users are the best bets for their ads. So advertisers buy a combination of information (from data providers) and advertising space (from publishers like Yahoo). How much should advertisers pay for each? Let's have a hands-on experience to find out.

Validating Network Classifiers: Networks are fundamental to our lives, from the network of gene interactions that shapes our bodies to the social networks that can eat up the hours of our lives. :-) Collective classification uses network structure to predict node information. For example, if your friends all like jazz, are you likely to as well? Since networks grow by adding nodes based on the nodes already in the network, nodes are not drawn i.i.d. This makes trouble for most machine learning approaches to validation of classifier performance. We will discuss a method to validate network classifiers that is based on understanding how the network grows.

Bio:

Eric Bax does research in machine learning, algorithms, and economics. He has a PhD from Caltech and a BS from Furman University. He has taught math and computer science as a Peace Corps volunteer in Botswana and as a professor at University of Richmond. He has worked at iSpheres, Applied Minds, Google, and Yahoo.