Ensemble learning is attracting much attention from pattern recognition and machine learning domains for good generalization. Both theoretical and experimental researches show tha...
We aim at merging technologies from information technology, roomware, and robotics in order to design adaptive and intelligent furniture. This paper presents design principles for ...
—Subspaces offer convenient means of representing information in many pattern recognition, machine vision, and statistical learning applications. Contrary to the growing populari...
We describe the integration of smart digital objects with Hebbian learning to create a distributed, real-time, scalable approach to adapting to a community's preferences. We ...
Thomas Lutkenhouse, Michael L. Nelson, Johan Bolle...
We present a mixture model based approach for learning individualized behavior models for the Web users. We investigate the use of maximum entropy and Markov mixture models for ge...