Nearest neighbor searching is a fundamental building block of most sampling-based motion planners. We present a novel method for fast exact nearest neighbor searching in SE(3)—the 6 dimensional space that represents rotations and translations in 3 dimensions. SE(3) is commonly used when planning the motions of rigid body robots. Our approach starts by projecting a 4-dimensional cube onto the 3-...

This paper studies nearest neighbor classification in a model where unlabeled data points arrive in a stream, and the learner decides, for each one, whether to ask for its label. Are there generic ways to augment or modify any selective sampling strategy so as to ensure the consistency of the resulting nearest neighbor classifier?

Decision making from sequential sampling, especially when more than two alternative choices are possible, requires appropriate stopping criteria to maximize accuracy under time constraints. Optimal conditions for stopping have previously been investigated for modeling human decision making processes. In this work, we show how the k-nearest neighbor classification algorithm in machine learning c...