The efficiency–accuracy trade-off of approximate computing spans a diverse array of techniques at both the hardware and software levels. While this diversity is key to the success of approximation research, it also entails considerable complexity in developing and validating new approximation techniques. Researchers must relate their ideas to a vast body of work on approximate computing and inv...

In this paper we give the first, to our knowledge, structures and corresponding algorithms for approximate indexing, by considering the Hamming distance, having the following properties. i) Their size is linear times a polylog of the size of the text on average. ii) For each pattern x, the time spent by our algorithms for finding the list occ(x) of all occurrences of a pattern x in the text, up...

Approximate computing has shown to provide new ways to improve performance and power consumption of errorresilient applications. While many of these applications can be found in image processing, data classification or machine learning, we demonstrate its suitability to a problem from scientific computing. Utilizing the self-correcting behavior of iterative algorithms, we show that approximate ...

Approximate entropy (ApEn) adapted to quantify the pattern complexity across the electro-glottogram (EGG) spectral domain characterizes normal male vowel phonation in two groups, a majority group (G1) with high ApEn and a minority group (G2) with low ApEn. Using the ApEn measure of normality a sample of post-treatment male oncology patients with adult onset growth hormone deficiency (GHD) shows...

In this paper we present an approach to terminology recognition whereby a sublanguage term (e.g. an aircraft engine component term extracted from a maintenance log) is matched to its corresponding term from a pre-defined list (such as a taxonomy representing the official break-down of the engine). Terminology recognition is addressed as a classification task whereby the extracted term is associ...

A left ideal of any C∗-algebra is an example of an operator algebra with a right contractive approximate identity (r.c.a.i.). Conversely, we show here and in [6] that operator algebras with r.c.a.i. should be studied in terms of a certain left ideal of a C∗-algebra. We study operator algebras and their multiplier algebras from the perspective of ‘Hamana theory’ and using the multiplier algebras...

Large templated factor graphs with complex structure that changes during inference have been shown to provide state-of-the-art experimental results in tasks such as identity uncertainty and information integration. However, inference and learning in these models is notoriously difficult. This paper formalizes, analyzes and proves convergence for the SampleRank algorithm, which learns extremely ...

We show that inverse problems with a truncated quadratic regularization are NP-hard in general to solve or even approximate up to an additive error. This stands in contrast to the case corresponding to a finite-dimensional approximation to the Mumford-Shah functional, where the operator involved is the identity and for which polynomial-time solutions are known. Consequently, we confirm the infe...

In this paper we study several aspects of solitary wave solutions of the Ostrovsky equation. Using variational methods, we show that as the rotation parameter goes to zero, ground state solitary waves of the Ostrovsky equation converge to solitary waves of the Korteweg-deVries equation. We also investigate the properties of the function d(c) which determines the stability of the ground states. ...

An expansion based on renormalization group methods for the spin correlation function in the z direction of the Heisenberg-Ising XY Z chain with an external magnetic field directed as the z axis is derived. Moreover, by using the hidden symmetries of the model, we show that the running coupling constants are small, if the coupling in the z direction is small enough, that a critical index appear...