Modeling the perceived behaviors of other agents improves the performance of an agent in multiagent interactions. We utilize the language of interactive influence diagrams to mode...
We introduce a method that enables scalable image search for learned metrics. Given pairwise similarity and dissimilarity constraints between some images, we learn a Mahalanobis d...
The k-Nearest Neighbors algorithm can be easily adapted to classify complex objects (e.g. sets, graphs) as long as a proper dissimilarity function is given over an input space. Bo...
Adam Woznica, Alexandros Kalousis, Melanie Hilario
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
We develop a theory for learning scenarios where multiple learners co-exist but there are mutual compatibility constraints on their outcomes. This is natural in cognitive learning...