It is commonly appreciated that solving search problems optimally can take too long. Bounded suboptimal search algorithms trade increased solution cost in a principled way for reduced solving time. Explicit Estimation Search (EES) is a recent state-of-the-art algorithm for bounded suboptimal search. Although it tends to expand fewer nodes than alternative algorithms, its per-node expansion over...

In this paper, we analyze the performance of weighted 1 minimization over a non-uniform sparse signal model by extending the “Gaussian width” analysis proposed in [1]. Our results are consistent with those of [7] which are currently the best known ones. However, our methods are less computationally intensive and can be easily extended to signals which have more than two sparsity classes. Finall...

Backward simulation relations provide a technique for verifying computer systems modelled as labelled transition systems. Recent experience suggests that backward simulation relations are useful in the verification of some highly concurrent systems. Proofs by backward simulation are complicated by the need to show that the simulation relation is total over all reachable states of the system bei...

Network science plays a central role in the study of complex systems, offering a range of computational tools and, importantly, a common language to represent systems as diverse as the World Wide Web, the human brain, and social networks (1). Within the framework of network science, a system is modeled as a set of nodes, representing the individual units of the system, and a set of links, repre...

We give a new, manifestly spacetime-supersymmetric method for calculating superstring scattering amplitudes, using the ghost pyramid, that is simpler than all other known methods. No pictures nor non-vertex insertions are required other than the usual b and c ghosts of the bosonic string. We evaluate some tree and loop amplitudes as examples. [email protected] and [email protected]...

Abstract The typical method of solving for the optimal nonlinear tax schedule relies on deriving incentive-compatible allocations. While this “primal approach” is mathematically rigorous, it lacks intuitive appeal. This paper considers a different that directly system. “dual much closer to actual policy as centers around welfare effects reforms. I show can easily incorporate preference heteroge...

We built three different AI models to predict the category (frozen, liquid or none) based on polarimetric radar variables. One model was a long-shot model for the purpose of winning the competition (it didn’t). The second was a complex black box model to represent the average learnability of the dataset. The third was a simple, human-readable model that would perform similarly to the above two ...