We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...
In this paper, we present SISYPHUS, a storage manager for data cubes that provides an efficient physical base for performing OLAP operations. On-Line Analytical Processing (OLAP) ...
This paper presents a novel approach for reconstructing free-form, texture-mapped, 3D scene models from a single painting or photograph. Given a sparse set of user-specified const...
Li Zhang, Guillaume Dugas-Phocion, Jean-Sebastien ...
This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
Abstract—This paper develops an algorithm for NMR backbone resonance assignment given a 3D structure and a set of relatively sparse 15 N-edited NMR data, with the through-space 1...