Transfer learning is the ability of an agent to apply knowledge learned in previous tasks to new problems or domains. We approach this problem by focusing on model formulation, i....
Abstract. Finding solutions to minimal problems for estimating epipolar geometry and camera motion leads to solving systems of algebraic equations. Often, these systems are not tri...
Abstract. The trace quotient problem arises in many applications in pattern classification and computer vision, e.g., manifold learning, low-dimension embedding, etc. The task is ...
Constraint Programming is a powerful approach for modeling and solving many combinatorial problems, scalability, however, remains an issue in . Abstraction and reformulation techni...
Kenneth M. Bayer, Martin Michalowski, Berthe Y. Ch...
Leader election and arbitrary pattern formation are fundammental tasks for a set of autonomous mobile robots. The former consists in distinguishing a unique robot, called the lead...