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558
The Capacity of Low-Density Parity-Check Codes Under Message-Passing Decoding
, 2001
"... In this paper, we present a general method for determining the capacity of low-density parity-check (LDPC) codes under message-passing decoding when used over any binary-input memoryless channel with discrete or continuous output alphabets. Transmitting at rates below this capacity, a randomly chos ..."
Abstract
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Cited by 574 (9 self)
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In this paper, we present a general method for determining the capacity of low-density parity-check (LDPC) codes under message-passing decoding when used over any binary-input memoryless channel with discrete or continuous output alphabets. Transmitting at rates below this capacity, a randomly
Efficient Encoding of Low-Density Parity-Check Codes
, 2001
"... Low-density parity-check (LDPC) codes can be considered serious competitors to turbo codes in terms of performance and complexity and they are based on a similar philosophy: constrained random code ensembles and iterative decoding algorithms. In this paper, we consider the encoding problem for LDPC ..."
Abstract
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Cited by 183 (3 self)
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Low-density parity-check (LDPC) codes can be considered serious competitors to turbo codes in terms of performance and complexity and they are based on a similar philosophy: constrained random code ensembles and iterative decoding algorithms. In this paper, we consider the encoding problem
EXE: Automatically generating inputs of death
- In Proceedings of the 13th ACM Conference on Computer and Communications Security (CCS
, 2006
"... This article presents EXE, an effective bug-finding tool that automatically generates inputs that crash real code. Instead of running code on manually or randomly constructed input, EXE runs it on symbolic input initially allowed to be anything. As checked code runs, EXE tracks the constraints on ea ..."
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Cited by 349 (21 self)
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This article presents EXE, an effective bug-finding tool that automatically generates inputs that crash real code. Instead of running code on manually or randomly constructed input, EXE runs it on symbolic input initially allowed to be anything. As checked code runs, EXE tracks the constraints
Cost-Constrained Random Coding and Applications
"... Abstract—This paper studies a random coding ensemble in which each codeword is constrained to satisfy multiple cost constraints. Using this ensemble, an achievable second-order coding rate is presented for the mismatched single-user channel. Achievable error exponents are given for the mismatched si ..."
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Abstract—This paper studies a random coding ensemble in which each codeword is constrained to satisfy multiple cost constraints. Using this ensemble, an achievable second-order coding rate is presented for the mismatched single-user channel. Achievable error exponents are given for the mismatched
The Mismatched Multiple-Access Channel: General Alphabets
"... Abstract-This paper considers channel coding for the memoryless multiple-access channel with a given (possibly suboptimal) decoding rule. Non-asymptotic bounds on the error probability are given, and a cost-constrained random-coding ensemble is used to obtain an achievable error exponent. The achie ..."
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Abstract-This paper considers channel coding for the memoryless multiple-access channel with a given (possibly suboptimal) decoding rule. Non-asymptotic bounds on the error probability are given, and a cost-constrained random-coding ensemble is used to obtain an achievable error exponent
Entropy of random graph ensembles constrained with
"... Abstract. Generalised degrees provide a natural bridge between local and global topological properties of networks. We define the generalised degree (k,m) to be the number of neighbours of a node within one and two steps respectively. Tailored random graph ensembles are used to quantify and compare ..."
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topological properties of networks in a systematic and precise manner, using concepts from information theory. We calculate the Shannon entropy of random graph ensembles constrained with a specified generalised degree distribution. We find that the outcome has a natural connection with the degree
Level Repulsion in Constrained Gaussian Random–Matrix Ensembles
, 2006
"... Abstract. Introducing sets of constraints, we define new classes of random–matrix ensembles, the constrained Gaussian unitary (CGUE) and the deformed Gaussian unitary (DGUE) ensembles. The latter interpolate between the GUE and the CGUE. We derive a sufficient condition for GUE–type level repulsion ..."
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Abstract. Introducing sets of constraints, we define new classes of random–matrix ensembles, the constrained Gaussian unitary (CGUE) and the deformed Gaussian unitary (DGUE) ensembles. The latter interpolate between the GUE and the CGUE. We derive a sufficient condition for GUE–type level repulsion
F.: Fast discriminative visual codebooks using randomized clustering forests
- In: Advances in Neural Information Processing Systems
, 2006
"... Some of the most effective recent methods for content-based image classifica-tion work by extracting dense or sparse local image descriptors, quantizing them according to a coding rule such as k-means vector quantization, accumulating his-tograms of the resulting “visual word ” codes over the image, ..."
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Cited by 156 (4 self)
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, and classifying these with a conventional classifier such as an SVM. Large numbers of descriptors and large codebooks are needed for good results and this becomes slow using k-means. We introduce Extremely Randomized Clustering Forests – ensembles of randomly created clustering trees – and show that these provide
Mismatched Decoding: Error Exponents, Second-Order Rates and Saddlepoint Approximations
, 2014
"... This paper considers the problem of channel coding with a given (possibly suboptimal) maximum-metric decoding rule. A cost-constrained random-coding ensemble with multiple auxiliary costs is introduced, and is shown to achieve error expo-nents and second-order coding rates matching those of consta ..."
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This paper considers the problem of channel coding with a given (possibly suboptimal) maximum-metric decoding rule. A cost-constrained random-coding ensemble with multiple auxiliary costs is introduced, and is shown to achieve error expo-nents and second-order coding rates matching those
Results 1 - 10
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558
