We consider two basic computational problems regarding discrete probability distributions: (1) approximating the statistical difference (aka variation distance) between two given d...
We consider the problem of designing a near-optimal linear decision tree to classify two given point sets B and W in n. A linear decision tree de nes a polyhedral subdivision of sp...
Michelangelo Grigni, Vincent Mirelli, Christos H. ...
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
One of the challenges in geometry processing is to automatically reconstruct a higher-level representation from raw geometric data. For instance, computing a parameterization of a...
In this paper we study the long standing problem of information extraction from multiple linear approximations. We develop a formal statistical framework for block cipher attacks b...