We derive a family of kernels on dynamical systems by applying the Binet-Cauchy theorem to trajectories of states. Our derivation provides a unifying framework for all kernels on d...
S. V. N. Vishwanathan, Alexander J. Smola, Ren&eac...
This paper examines the problem of estimating linear time-invariant state-space system models. In particular it addresses the parametrization and numerical robustness concerns tha...
Linear and kernel discriminant analyses are popular approaches for supervised dimensionality reduction. Uncorrelated and regularized discriminant analyses have been proposed to ove...
Very large and geometrically complex scenes, exceeding millions of polygons and hundreds of objects, arise naturally in many areas of interactive computer graphics. Time-critical ...
Abstract. This paper proposes an entropy based Markov chain (EMC) fusion technique and demonstrates its applications in multisensor fusion. Self-entropy and conditional entropy, wh...