Distributed W-Learning (DWL) is a reinforcement learningbased algorithm for multi-policy optimization in agent-based systems. In this poster we propose the use of DWL for decentra...
Canonical problems are simplified representations of a class of real world problems. They allow researchers to compare algorithms in a standard setting which captures the most im...
Matrix factorization (MF) models have proved efficient and well scalable for collaborative filtering (CF) problems. Many researchers also present the probabilistic interpretation o...
Choosing good features to represent objects can be crucial to the success of supervised machine learning algorithms. Good high-level features are those that concentrate informatio...
In this paper, we present a framework for immersive 3D video conferencing and geographically distributed collaboration. Our multi-camera system performs a full-body 3D reconstruct...
Gregorij Kurillo, Ramanarayan Vasudevan, Edgar J. ...