A greedy-based approach to learn a compact and discriminative dictionary for sparse representation is presented. We propose an objective function consisting of two components: ent...
We propose a latent variable model to enhance historical analysis of large corpora. This work extends prior work in topic modelling by incorporating metadata, and the interactions...
William Yang Wang, Elijah Mayfield, Suresh Naidu, ...
Many large-scale parallel programs follow a bulk synchronous parallel (BSP) structure with distinct computation and communication phases. Although the communication phase in such ...
Torsten Hoefler, Christian Siebert, Andrew Lumsdai...
Much recent work has concerned sparse approximations to speed up the Gaussian process regression from the unfavorable O(n3 ) scaling in computational time to O(nm2 ). Thus far, wo...
Abstract. We show a two-phase approach for minimizing various communication-cost metrics in fine-grain partitioning of sparse matrices for parallel processing. In the first phase...