Our novel methodology, called PVA, which is a manifold learning approach for nonlinear dimensionality reduction and data modeling got accepted in the 2017 Annual Conference on Robot Learning as a full-length talk (acceptance rate for full-length talk papers was 10.59%). PVA is expected to make a significant breakthrough in various applications, such as robotics and etc.
