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Wordsize Parallelism
"... this paper we generalize such a parallelism by using larger blocks of bits. The parallelism has, with latest 32 and 64 bit generation of processors, even greater practical significance (cf. [7]). In order, to make our results more general we denote the word size by m. Next, we use the notation ..."
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this paper we generalize such a parallelism by using larger blocks of bits. The parallelism has, with latest 32 and 64 bit generation of processors, even greater practical significance (cf. [7]). In order, to make our results more general we denote the word size by m. Next, we use the notation
A comparison of event models for Naive Bayes text classification
, 1998
"... Recent work in text classification has used two different firstorder probabilistic models for classification, both of which make the naive Bayes assumption. Some use a multivariate Bernoulli model, that is, a Bayesian Network with no dependencies between words and binary word features (e.g. Larkey ..."
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Cited by 1025 (26 self)
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Recent work in text classification has used two different firstorder probabilistic models for classification, both of which make the naive Bayes assumption. Some use a multivariate Bernoulli model, that is, a Bayesian Network with no dependencies between words and binary word features (e
Parallel Networks that Learn to Pronounce English Text
 COMPLEX SYSTEMS
, 1987
"... This paper describes NETtalk, a class of massivelyparallel network systems that learn to convert English text to speech. The memory representations for pronunciations are learned by practice and are shared among many processing units. The performance of NETtalk has some similarities with observed h ..."
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Cited by 549 (5 self)
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human performance. (i) The learning follows a power law. (;i) The more words the network learns, the better it is at generalizing and correctly pronouncing new words, (iii) The performance of the network degrades very slowly as connections in the network are damaged: no single link or processing unit
Estimation of probabilities from sparse data for the language model component of a speech recognizer
 IEEE Transactions on Acoustics, Speech and Signal Processing
, 1987
"... AbstractThe description of a novel type of rngram language model is given. The model offers, via a nonlinear recursive procedure, a computation and space efficient solution to the problem of estimating probabilities from sparse data. This solution compares favorably to other proposed methods. Wh ..."
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Cited by 799 (2 self)
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, and it is a problem that one always encounters while collecting frequency statistics on words and word sequences (mgrams) from a text of finite size. This means that even for a very large data collection, the maximum likelihood estimation method does not allow Turing’s estimate PT for a probability of a
Understanding and using the Implicit Association Test: I. An improved scoring algorithm
 Journal of Personality and Social Psychology
, 2003
"... behavior relations Greenwald et al. Predictive validity of the IAT (Draft of 30 Dec 2008) 2 Abstract (131 words) This review of 122 research reports (184 independent samples, 14,900 subjects), found average r=.274 for prediction of behavioral, judgment, and physiological measures by Implic ..."
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Cited by 632 (94 self)
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behavior relations Greenwald et al. Predictive validity of the IAT (Draft of 30 Dec 2008) 2 Abstract (131 words) This review of 122 research reports (184 independent samples, 14,900 subjects), found average r=.274 for prediction of behavioral, judgment, and physiological measures
Text Classification using String Kernels
"... We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A subsequence is any ordered sequence of k characters occurring in the text though not necessarily contiguo ..."
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Cited by 495 (7 self)
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the dimension of the feature space grows exponentially with k. The paper describes how despite this fact the inner product can be e ciently evaluated by a dynamic programming technique. Experimental comparisons of the performance of the kernel compared with a standard word feature space kernel Joachims (1998
Efficient code generation for ASIPs with different word sizes
 In proceedings of the third conference of the Advanced School for Computing and Imaging
, 1997
"... We propose a complete methodology for extending our automatic ASIP (Architecture Specific Instruction set Processor) synthesis framework to a much wider target architecture space. In this new architecture space the width of the integer data word and of any hardware resource data path is userdefinab ..."
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Cited by 4 (2 self)
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We propose a complete methodology for extending our automatic ASIP (Architecture Specific Instruction set Processor) synthesis framework to a much wider target architecture space. In this new architecture space the width of the integer data word and of any hardware resource data path is user
Efficient code generation for ASIPs with different word sizes
 In proceedings of the third conference of the Advanced School for Computing and Imaging
, 1997
"... We propose a complete methodology for extending our automatic ASIP (Architecture Specific Instruction set Processor) synthesis framework to a much wider target architecture space. In this new architecture space the width of the integer data word and of any hardware resource data path is userdefinab ..."
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We propose a complete methodology for extending our automatic ASIP (Architecture Specific Instruction set Processor) synthesis framework to a much wider target architecture space. In this new architecture space the width of the integer data word and of any hardware resource data path is user
An Investigation of Complex Operations with WordSize Homomorphic Encryption
"... Abstract. Homomorphic encryption has progressed rapidly in both efficiency and versatility since its emergence in 2009. Meanwhile, a multitude of pressing privacy needs — ranging from cloud computing to healthcare management to the handling of shared databases such as those containing genomics dat ..."
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data — call for immediate solutions that apply fully homomorpic encryption (FHE) and somewhat homomorphic encryption (SHE) technologies. Further progress towards these ends requires new ideas for the efficient implementation of algebraic operations on wordbased (as opposed to bitwise) encrypted data
A Theory of Program Size Formally Identical to Information Theory
, 1975
"... A new definition of programsize complexity is made. H(A;B=C;D) is defined to be the size in bits of the shortest selfdelimiting program for calculating strings A and B if one is given a minimalsize selfdelimiting program for calculating strings C and D. This differs from previous definitions: (1) ..."
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Cited by 380 (15 self)
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A new definition of programsize complexity is made. H(A;B=C;D) is defined to be the size in bits of the shortest selfdelimiting program for calculating strings A and B if one is given a minimalsize selfdelimiting program for calculating strings C and D. This differs from previous definitions: (1
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