Learning from structured data is becoming increasingly important. However, most prior work on kernel methods has focused on learning from attribute-value data. Only recently, rese...
Adam Kowalczyk, Alex J. Smola, Peter A. Flach, Tho...
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
SemanticOrganizer is a collaborative knowledge management system designed to support distributed NASA projects, including multidisciplinary teams of scientists, engineers, and acci...
Richard M. Keller, Daniel C. Berrios, Robert E. Ca...
As suggested by the title of Shoham, Powers, and Grenager’s position paper [34], the ultimate lens through which the multi-agent learning framework should be assessed is “what...
Multiagent learning can be seen as applying ML techniques to the core issues of multiagent systems, like communication, coordination, and competition. In this paper, we address the...