We are concerned with kernel density estimation on the rotation group SO(3). We prove asymptotically optimal convergence rates for the minimax risk of the mean integrated squared error for different function classes including bandlimited functions, functions with bounded Sobolev norm and functions with polynomial decaying Fourier coefficients and give optimal kernel functions. Furthermore, we c...

Kernel functions have become an extremely popular tool in machine learning, with many applications and an attractive theory [1, 12, 10]. There has also been substantial work on learning kernel functions from data [7, 11, 2]. A sufficient condition for a kernel to allow for good generalization on a given learning problem is that it induce a large margin of separation between positive and negativ...

As one of the supervised tensor learning methods, support machine (STM) for tensorial data classification is receiving increasing attention in and related applications, including remote sensing imaging, video processing, fault diagnosis, etc. Existing STM approaches lack consideration tensors terms reduction. To address this deficiency, we built a novel sparse model to control number binary dat...