In this paper, we propose a bilevel sparse coding model for coupled feature spaces, where we aim to learn dictionaries for sparse modeling in both spaces while enforcing some desi...
We give efficient algorithms to sample uniformly, and count approximately, the solutions to a zero-one knapsack problem. The algorithm is based on using dynamic programming to pro...
We initiate a novel study of clustering problems. Rather than specifying an explicit objective function to optimize, our framework allows the user of clustering algorithm to speci...
We present two novel perturbation-based linkage learning algorithms that extend LINC [5]; a version of LINC optimised for decomposition tasks (oLINC) and a hierarchical version of...
High Resolution (HR) methods are known to provide accurate frequency estimates for discrete spectra. The Polynomial Amplitude Complex Exponentials (PACE) model, also called quasipo...