Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
We consider the problem of identifying the consensus ranking for the results of a query, given preferences among those results from a set of individual users. Once consensus ranki...
Paul N. Bennett, David Maxwell Chickering, Anton M...
We introduce the notion of query substitution, that is, generating a new query to replace a user's original search query. Our technique uses modifications based on typical su...
Rosie Jones, Benjamin Rey, Omid Madani, Wiley Grei...
Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...
In this work, we address the problem of joint modeling of text and citations in the topic modeling framework. We present two different models called the Pairwise-Link-LDA and the ...
Ramesh Nallapati, Amr Ahmed, Eric P. Xing, William...