There has been significant interest in developing new forms of acoustic model, in particular models which allow additional dependencies to be represented than those contained within a standard hidden Markov model (HMM). This paper discusses one such class of models, augmented statistical models. Here, a local exponential approximation is made about some point on a base model. This allows additi...

ANDRILL completed its first season in 2006-07 drilling AND-1B through the McMurdo Ice Shelf (MIS) to a depth of 1,285m below the sea floor, a record for Antarctic margin drilling, with 99% recovery. The alternating glacial-interglacial sediment packages interbedded with volcanics provide a uniquely detailed record of Antarctic glacial and climatic change through the Neogene. This paper summariz...

In [4] an algorithm is presented for analytic phase margin control design. Without special care, however, the compensator computed with this algorithm may not be a real rational function. The problem is evident when the plant has real unstable poles. In this case the algorithm in [4] requires a mapping of real points into complex values, and it is not clear that the resulting compensator has re...

In this document we give a short overview of the reasons why Rijndael should be selected as the AES. We have divided our arguments into four categories: • Security: Rijndael has the same objective security level as the other finalists, and can easily be implemented in a secure way. • Efficiency: Rijndael has a large "performance margin" compared to the other candidates. • Design philosophy: The...

1 The central problem in the case of face detectors is to build a face class model. We present a method for face class modeling in the eigenfaces space using a large-margin classifier like SVM. Two main issues are addressed: what is the required number of eigenfaces to achieve a good classification rate and how to train the SVM for a good generalization. As the experimental evidence show, gener...

Sauer’s Lemma is extended to classes HN of binary-valued functions h on [n] = {1, . . . , n} which have a margin less than or equal to N on all x ∈ [n] with h(x) = 1, where the margin μh(x) of h at x ∈ [n] is defined as the largest non-negative integer a such that h is constant on the interval Ia(x) = [x− a, x+ a] ⊆ [n]. Estimates are obtained for the cardinality of classes of binary valued fun...

A family of classification algorithms generated from Tikhonov regularization schemes are considered. They involve multi-kernel spaces and general convex loss functions. Our main purpose is to provide satisfactory estimates for the excess misclassification error of these multi-kernel regularized classifiers. The error analysis consists of two parts: regularization error and sample error. Allowin...

high and increasing beef marketing margin leads one to controversy about factors affecting it. this study using the monthly data for the 1998-2005 period to investigate the market power and to estimate how farm and marketing services supplies and retail demand determinants can affect beef marketing margin. the results show that farm, marketing services and retail level prices and thereby ma...

In this article we study the generalization abilities of several classifiers of support vector machine (SVM) type using a certain class of kernels that we call universal. It is shown that the soft margin algorithms with universal kernels are consistent for a large class of classification problems including some kind of noisy tasks provided that the regularization parameter is chosen well. In pa...

We show that support vector machines of the 1-norm soft margin type are universally consistent provided that the regularization parameter is chosen in a distinct manner and the kernel belongs to a specific class}the so-called universal kernels}which has recently been considered by the author. In particular it is shown that the 1-norm soft margin classifier with Gaussian RBF kernel on a compact ...