3 accepted papers
Vision Mamba models have been extensively researched in various fields, which address the limitations of previous models by effectively managing long-range dependencies with a linear-time overhead. Several prospective studies have further designed Vision Mamba based on UNet(VM-UNet) for medical imag…
Large tensor learning algorithms are typically computationally expensive and require storing a vast amount of data. In this paper, we propose a unified online Riemannian gradient descent (oRGrad) algorithm for tensor learning, which is computationally efficient, consumes much less memory, and can ha…
We study the contextual bandits with knapsack (CBwK) problem under the high-dimensional setting where the dimension of the feature is large. We investigate how to exploit the sparsity structure to achieve improved regret for the CBwK problem. To this end, we first develop an online variant of the ha…