This paper presents a statistical learning approach to predicting people's bidding behavior in negotiation. Our study consists of multiple 2-player negotiation scenarios wher...
The explosion of Web opinion data has made essential the need for automatic tools to analyze and understand people’s sentiments toward different topics. In most sentiment analy...
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
This paper investigates an approach to model the space of brain images through a low-dimensional manifold. A data driven method to learn a manifold from a collections of brain imag...
Samuel Gerber, Tolga Tasdizen, Sarang C. Joshi, Ro...
In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...