We present a new family of linear time algorithms based on sufficient statistics for string comparison with mismatches under the string kernels framework. Our algorithms improve t...
Finite element simulations in computer graphics are typically based on tetrahedral or hexahedral elements, which enables simple and efficient implementations, but in turn requires...
Sebastian Martin, Peter Kaufmann, Mario Botsch, Ma...
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
The paper studies the problem of distributed static parameter (vector) estimation in sensor networks with nonlinear observation models and imperfect inter-sensor communication. We...
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...