A fuzzy extractor (Dodis et al., Eurocrypt 2004) is a pair of procedures that turns a noisy secret into a uniformly distributed key R. To eliminate noise, the generation procedure takes as input an enrollment value ω and outputsR and a helper string P that enables further reproduction ofR from some close reading ω′. Boyen highlighted the need for reusable fuzzy extractors (CCS 2004) that remain...

The standard notion of a randomness extractor is a procedure which converts any weak source of randomness into an almost uniform distribution. The conversion necessarily uses a small amount of pure randomness, which can be eliminated by complete enumeration in some, but not all, applications. Here, we consider the problem of deterministically converting a weak source of randomness into an almos...

In the previous lecture, we introduced the notion of a randomness extractor —a procedure which extracts " uniform " randomness from a weak random source and a small number of truly random bits. In this lecture, we give general impossibility results for randomness extraction. The results are taken from [NZ96, RT00]. We seek to characterize the class of random sources for which extraction is poss...

~ Recently, a minimum classification error training algorithm has been proposed for minimizing the misclassification probability based on a given set of training samples using a generalized probabilistic descent method. This algorithm is a type of discriminative learning algorithm, but it approaches the objective of minimum classification error in a more direct manner than the conventional disc...

Electronic Music Distribution (EMD) is in demand of robust, automatically extracted music descriptors. We introduce a timbral similarity measures for comparing music titles. This measure is based on a Gaussian model of cepstrum coefficients. We describe the timbre extractor and the corresponding timbral similarity relation. We describe experiments in assessing the quality of the similarity rela...

In this article, a Web services network extractor toolkit, WS-NEXT (WS Network EXtractor Toolkit), is presented. WS-NEXT allows extraction of interaction and dependency WS networks. Networks can be extracted from syntactic and semantic WS descriptions. Such network structures can be analyzed using complex network tools. We provide examples of networks extracted from a publicly available WS coll...

The paper describes a neural network-based script identification system which can be used in the machine reading of documents written in English, Hindi and Kannada language scripts. Script identification is a basic requirement in automation of document processing, in multi-script, multi-lingual environments. The system developed includes a feature extractor and a modular neural network. The fea...

Term extraction is an important problem in natural language processing. In this paper, we propose a language independent statistical corpus-based term extraction algorithm. In previous approaches, evaluation has been subjective, at best relying on a lexicographer’s judgement. We evaluate the quality of our term extractor by assessing its predictiveness on an unseen corpus using perplexity. Seco...

The University of Washington participated in Cold Start Slot Filling for TAC-KBP 2015 with a system that combines three methods: 1) its 2013 OPENIE-KBP system (Soderland et al., 2013); 2) a novel Implicit Relation Information Extractor (IMPLIE); and 3) MULTIR extractor (Hoffmann et al., 2011), trained on a combination of distant supervision and crowdsourced training instances. These three metho...

The lithium beam diagnostic at ASDEX Upgrade routinely delivers electron density profiles in the plasma edge by lithium beam impact excitation spectroscopy. An accurate background subtraction requires a periodically chopped lithium beam. A new, improved chopping system was developed and installed. It involves a voltage modulation for the extractor electrode and the beam deflection plates. The m...