The class of algorithms for approximating reasoning tasks presented in this paper is based on approximating the general bucket elimination framework. The algorithms have adjustabl...
Sequential pattern mining is an important data mining method with broad applications that can extract frequent sequences while maintaining their order. However, it is important to ...
We propose a novel, geometrically adaptive method for surface reconstruction from noisy and sparse point clouds, without orientation information. The method employs a fast convecti...
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
We present cache-oblivious solutions to two important variants of range searching: range reporting and approximate range counting. Our main contribution is a general approach for ...