We present methods for training high quality object detectors
very quickly. The core contribution is a pair of fast
training algorithms for piece-wise linear classifiers, which
...
Considering the statistical text classification problem we approximate class-conditional probability distributions by structurally modified Poisson mixtures. By introducing the st...
We present a discrete-time time-domain vector fitting algorithm, called TD-VFz, for rational function macromodeling of port-to-port responses with discrete time-sampled data. The ...
Abstract. We study the approximation of the integration of multivariate functions classes in the quantum model of computation. We first obtain a lower bound of the n-th minimal qu...
We study the capacity allocation problem in service overlay networks (SON)s with state-dependent connection routing based on revenue maximization. We formulate the dimensioning pro...