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454
Approximation Algorithms for Probabilistic Decoding
 In Uncertainty in Artificial Intelligence (UAI98
, 1998
"... It was recently shown that the problem of decoding messages transmitted through a noisy channel can be formulated as a belief updating task over a probabilistic network [13]. Moreover, it was observed that iterative application of the (linear time) belief propagation algorithm designed for polytr ..."
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Cited by 8 (5 self)
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It was recently shown that the problem of decoding messages transmitted through a noisy channel can be formulated as a belief updating task over a probabilistic network [13]. Moreover, it was observed that iterative application of the (linear time) belief propagation algorithm designed
On two probabilistic decoding algorithms for binary linear codes
 IEEE Transactions on Information Theory
, 1991
"... A generalization of Sullivan inequality on the ratio of the probability of a linear code to that of any of its cosets is proved. Starting from this inequality, a sufficient condition for successful decoding of linear codes by a probabilistic method is derived. A probabilistic decoding algorithm for ..."
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Cited by 2 (0 self)
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A generalization of Sullivan inequality on the ratio of the probability of a linear code to that of any of its cosets is proved. Starting from this inequality, a sufficient condition for successful decoding of linear codes by a probabilistic method is derived. A probabilistic decoding algorithm
Probabilistic Decoding of LowDensity Cayley Codes
"... We report on some investigations into the behavior of a class of lowdensity codes constructed using algebraic techniques. Recent work shows expansion to be an essential property of the graphs underlying the lowdensity paritycheck codes first introduced by Gallager. In addition, it has recently be ..."
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Cited by 3 (0 self)
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probabilistic decoding algorithm. Preliminary results indicate that the performance of the explicit, algebraic expanders is comparable to that of random graphs in the case where each variable is associated with only two parity checks, while such codes are inferior to randomly generated codes with three or more
Empirical evaluation of approximation algorithms for probabilistic decoding
 In Uncertainty in AI (UAI'98
, 1998
"... It was recently shown that the problem of decoding messages transmitted through a noisy channel can be formulated as a belief updating task over a probabilistic network [14]. Moreover, it was observed that iterative application of the (linear time) belief propagation algorithm designed for polytrees ..."
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Cited by 11 (7 self)
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It was recently shown that the problem of decoding messages transmitted through a noisy channel can be formulated as a belief updating task over a probabilistic network [14]. Moreover, it was observed that iterative application of the (linear time) belief propagation algorithm designed
NOTES ON PROBABILISTIC DECODING OF PARITY CHECK CODES
"... model of a noisy channel. We start with an array of bits s = (s1,...,sK), where each sk ∈ {0,1}. This is our source message, and the length K is the “degrees of freedom.” We encode the source message s into a vector of bits x ∈ C, where C ⊆ {0,1} N and N ≥ K. A member of C is called a codeword, and ..."
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transmitted signal t and the received signal y is usually modelled by y = t + v, (1) where v is the noise vector. We assume the individual entries of v are independently and identically drawn from a Normal distribution with zero mean and variance σ 2. The object is to decode the received codeword y
Solving the Probabilistic Decoding Problems Using Evolutionary Computation Techniques
"... Abstract: The number of inference problems that can be tackled using the probabilistic inference methods is enormous. This paper introduces a new algorithm for solving the probabilistic inference model of the block decoding problem of linear codes. This problem arises on a class of stream ciphers an ..."
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Abstract: The number of inference problems that can be tackled using the probabilistic inference methods is enormous. This paper introduces a new algorithm for solving the probabilistic inference model of the block decoding problem of linear codes. This problem arises on a class of stream ciphers
Integrated Analysis of Speech and Images as a Probabilistic Decoding Process
 In Proc. ICPR
, 2002
"... Speech understanding and vision are the two most important modalities in humanhuman communication. However, the emulation of these by a computer faces fundamental difficulties due to noisy data, vague meanings, previously unseen objects or unheard words, occlusions, spontaneous speech effects, a ..."
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Cited by 1 (1 self)
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, and context dependence. Thus, the interpretation processes on both channels are highly errorprone. This paper presents a new perspective on the problem of relating speech and image interpretations as a probabilistic decoding process. It is shown that such an integration scheme is robust regarding partial
Incorporating nonlocal information into information extraction systems by Gibbs sampling
 IN ACL
, 2005
"... Most current statistical natural language processing models use only local features so as to permit dynamic programming in inference, but this makes them unable to fully account for the long distance structure that is prevalent in language use. We show how to solve this dilemma with Gibbs sampling, ..."
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Cited by 730 (25 self)
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, a simple Monte Carlo method used to perform approximate inference in factored probabilistic models. By using simulated annealing in place of Viterbi decoding in sequence models such as HMMs, CMMs, and CRFs, it is possible to incorporate nonlocal structure while preserving tractable inference. We
Probabilistic Analysis of Linear Programming Decoding
, 2008
"... We initiate the probabilistic analysis of linear programming (LP) decoding of lowdensity paritycheck (LDPC) codes. Specifically, we show that for a random LDPC code ensemble, the linear programming decoder of Feldman et al. succeeds in correcting a constant fraction of errors with high probabilit ..."
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Cited by 25 (6 self)
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We initiate the probabilistic analysis of linear programming (LP) decoding of lowdensity paritycheck (LDPC) codes. Specifically, we show that for a random LDPC code ensemble, the linear programming decoder of Feldman et al. succeeds in correcting a constant fraction of errors with high
Low Density Parity Check Codes over GF(q)
 IEEE COMMUNICATIONS LETTERS
, 1996
"... Gallager's low density parity check codes over GF (2) have been shown to have near Shannon limit performance when decoded using a probabilistic decoding algorithm. In this paper we report the empirical performance of the analogous codes defined over GF (q) for q > 2. ..."
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Cited by 122 (16 self)
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Gallager's low density parity check codes over GF (2) have been shown to have near Shannon limit performance when decoded using a probabilistic decoding algorithm. In this paper we report the empirical performance of the analogous codes defined over GF (q) for q > 2.
Results 1  10
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