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...
Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo
Sensornet lifespan and utility is limited by the energy resources of individual motes. Network designers seek to maximise energy efficiency while maintaining acceptable Quality o...
— A novel criterion is introduced for assessing the diversity of a collection of paths or trajectories. The main idea is the notion of survivability, which measures the likelihoo...
We present a novel dynamic programming framework that allows one to compute tight upper bounds for the p-values of gapped local alignments in pseudo–polynomial time. Our algorith...