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Correcting errors in shotgun sequences
 Nucleic Acids Res
, 2003
"... Sequencing errors in combination with repeated regions cause major problems in shotgun sequencing, mainly due to the failure of assembly programs to distinguish single base differences between repeat copies from erroneous base calls. In this paper, a new strategy designed to correct errors in shotgu ..."
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Cited by 10 (0 self)
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Sequencing errors in combination with repeated regions cause major problems in shotgun sequencing, mainly due to the failure of assembly programs to distinguish single base differences between repeat copies from erroneous base calls. In this paper, a new strategy designed to correct errors
Near Shannon limit errorcorrecting coding and decoding
, 1993
"... Abstract This paper deals with a new class of convolutional codes called Turbocodes, whose performances in terms of Bit Error Rate (BER) are close to the SHANNON limit. The TurboCode encoder is built using a parallel concatenation of two Recursive Systematic Convolutional codes and the associated ..."
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Cited by 1776 (6 self)
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Abstract This paper deals with a new class of convolutional codes called Turbocodes, whose performances in terms of Bit Error Rate (BER) are close to the SHANNON limit. The TurboCode encoder is built using a parallel concatenation of two Recursive Systematic Convolutional codes
Locating and Correcting Errors in Images
 IN PROC. ICIP
, 1997
"... Most image interpolation or extrapolation algorithms assume that the locations of the unknown pixels are known. In this paper we attempt to remove this restriction. More precisely, we propose an algorithm for locating the incorrect pixels of an image, assuming only partial knowledge of its Fourier t ..."
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Cited by 5 (1 self)
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Most image interpolation or extrapolation algorithms assume that the locations of the unknown pixels are known. In this paper we attempt to remove this restriction. More precisely, we propose an algorithm for locating the incorrect pixels of an image, assuming only partial knowledge of its Fourier transform. Note that this is a nonlinear problem: the unknown quantities are the positions and values of the (say) n erroneous pixels. We show that the positions can be evaluated in O(n²) or even O(n log n) flops by solving a set of n linear equations and computing a FFT. The determination of n is part of the algorithm, whose stability is also briefly discussed. The values of the n incorrect pixels can then be estimated using any of the interpolation methods known.
Locating and Correcting Errors in Images
, 1997
"... Most image interpolation or extrapolation algorithms assume that the locations of the unknown pixels are known. In this paper we attempt to remove this restriction. More precisely, we propose an algorithm for locating the incorrect pixels of an image, assuming only partial knowledge of its Fourier t ..."
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Most image interpolation or extrapolation algorithms assume that the locations of the unknown pixels are known. In this paper we attempt to remove this restriction. More precisely, we propose an algorithm for locating the incorrect pixels of an image, assuming only partial knowledge of its Fourier transform. Note that this is a nonlinear problem: the unknown quantities are the positions and values of the (say) n erroneous pixels. We show that the positions can be evaluated in O(n 2 ) or even O(n log n) flops by solving a set of n linear equations and computing a FFT. The determination of n is part of the algorithm, whose stability is also briefly discussed. The values of the n incorrect pixels can then be estimated using any of the interpolation methods known. 1 Notation The complex Ndimensional space, with the usual inner product and norm, is denoted by C N . The conjugate transpose is denoted by . The Fourier matrix F is the unitary N \Theta N matrix whose elements F ab are gi...
Solving multiclass learning problems via errorcorrecting output codes
 JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
, 1995
"... Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass l ..."
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Cited by 726 (8 self)
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output representations. This paper compares these three approaches to a new technique in which errorcorrecting codes are employed as a distributed output representation. We show that these output representations improve the generalization performance of both C4.5 and backpropagation on a wide range
Good ErrorCorrecting Codes based on Very Sparse Matrices
, 1999
"... We study two families of errorcorrecting codes defined in terms of very sparse matrices. "MN" (MacKayNeal) codes are recently invented, and "Gallager codes" were first investigated in 1962, but appear to have been largely forgotten, in spite of their excellent properties. The ..."
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Cited by 750 (23 self)
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We study two families of errorcorrecting codes defined in terms of very sparse matrices. "MN" (MacKayNeal) codes are recently invented, and "Gallager codes" were first investigated in 1962, but appear to have been largely forgotten, in spite of their excellent properties
Correcting Errors in RSA Private Keys
"... Abstract. Let pk = (N, e) be an RSA public key with corresponding secret key sk = (p, q, d, dp, dq, q −1 p). Assume that we obtain partial errorfree information of sk, e.g., assume that we obtain half of the most significant bits of p. Then there are wellknown algorithms to recover the full secret ..."
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Cited by 5 (0 self)
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secret key. As opposed to these algorithms that allow for correcting erasures of the key sk, we present for the first time a heuristic probabilistic algorithm that is capable of correcting errors in sk provided that e is small. That is, on input of a full but errorprone secret key ˜ sk we reconstruct
Estimating standard errors in finance panel data sets: comparing approaches.
 Review of Financial Studies
, 2009
"... Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solut ..."
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Cited by 890 (7 self)
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solutions to this problem. Corporate finance has relied on clustered standard errors, while asset pricing has used the FamaMacBeth procedure to estimate standard errors. This paper examines the different methods used in the literature and explains when the different methods yield the same (and correct
Correcting errors without leaking partial information
 In 37th Annual ACM Symposium on Theory of Computing (STOC
, 2005
"... This paper explores what kinds of information two parties must communicate in order to correct errors which occur in a shared secret string W. Any bits they communicate must leak a significant amount of information about W — that is, from the adversary’s point of view, the entropy of W will drop sig ..."
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Cited by 65 (9 self)
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This paper explores what kinds of information two parties must communicate in order to correct errors which occur in a shared secret string W. Any bits they communicate must leak a significant amount of information about W — that is, from the adversary’s point of view, the entropy of W will drop
Is There A New Way to Correct Errors
"... AbstractThe classic approach for error correction is to add controlled external redundancy to data. This approach, called errorcorrecting codes, has been studied extensively. And the rates of ECCs are approaching theoretical limits. We explore a second approach for error correction in this work, ..."
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AbstractThe classic approach for error correction is to add controlled external redundancy to data. This approach, called errorcorrecting codes, has been studied extensively. And the rates of ECCs are approaching theoretical limits. We explore a second approach for error correction in this work
Results 1  10
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