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1 Randomness and Computation Joint Workshop “New Horizons in Computing ” and “Statistical Mechanical Approach to Probabilistic
, 2005
"... A CDMA multiuser detection algorithm based on ..."
Randomness and Computation Joint Workshop “New Horizons in Computing ” and “Statistical Mechanical Approach to Probabilistic
"... On a definition of random sequences with respect to parametric models ..."
Randomness and Computation Joint Workshop “New Horizons in Computing ” and “Statistical Mechanical Approach to Probabilistic
"... On finding a guard that sees most and a shop that sells most 1 ..."
Randomness and Computation Joint Workshop “New Horizons in Computing ” and “Statistical Mechanical Approach to Probabilistic Information Processing ” (1821 July, 2005, Sendai, Japan) Dense subgraph problem revisited
"... We consider the weighted dense subgraph problem (often called the maximum dispersion problem or dense ksubgraph problem) defined as follows: Consider a weighted graph G =(V,E), where V  = n and each edge e has a nonnegative weight 0 ≤ w(e) ≤ 1. Given a natural numbers k ≤ n, find a subgraph H = ..."
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We consider the weighted dense subgraph problem (often called the maximum dispersion problem or dense ksubgraph problem) defined as follows: Consider a weighted graph G =(V,E), where V  = n and each edge e has a nonnegative weight 0 ≤ w(e) ≤ 1. Given a natural numbers k ≤ n, find a subgraph H =(X, F) ofG such that X  = k and w(F) = � e∈F w(e) is maximized. Its bipartite version is as follows: Consider a weighted bipartite graph G =(U, V, E), where U  = m, V  = n and each edge e has a nonnegative weight 0 ≤ w(e) ≤ 1. Given two natural numbers m ′ ≤ m and n ′ ≤ n, find a subgraph H =(X, Y, F) ofG such that X  = m ′ , Y  = n ′ and w(F) = � e∈F w(e) is maximized. We note the condition 0 ≤ w(e) ≤ 1 is given since it is convenient for presenting our theoretical results, although we can define each problem without this condition. We say unweighted dense subgraph problem if w(e) = 1 for each edge. We define the density ∆ of the output subgraph H to be ∆ =
Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
 Biometrika
, 1995
"... Markov chain Monte Carlo methods for Bayesian computation have until recently been restricted to problems where the joint distribution of all variables has a density with respect to some xed standard underlying measure. They have therefore not been available for application to Bayesian model determi ..."
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Cited by 1345 (23 self)
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Markov chain Monte Carlo methods for Bayesian computation have until recently been restricted to problems where the joint distribution of all variables has a density with respect to some xed standard underlying measure. They have therefore not been available for application to Bayesian model
Parameterized Complexity
, 1998
"... the rapidly developing systematic connections between FPT and useful heuristic algorithms  a new and exciting bridge between the theory of computing and computing in practice. The organizers of the seminar strongly believe that knowledge of parameterized complexity techniques and results belongs ..."
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Cited by 1213 (77 self)
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the rapidly developing systematic connections between FPT and useful heuristic algorithms  a new and exciting bridge between the theory of computing and computing in practice. The organizers of the seminar strongly believe that knowledge of parameterized complexity techniques and results belongs
Muscle: multiple sequence alignment with high accuracy and high throughput
 NUCLEIC ACIDS RES
, 2004
"... We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using treedependent r ..."
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Cited by 2509 (7 self)
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We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using tree
Using Bayesian networks to analyze expression data
 Journal of Computational Biology
, 2000
"... DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a “snapshot ” of transcription levels within the cell. A major challenge in computational biology is to uncover, from such measurements, gene/protein interactions and key biologica ..."
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Cited by 1088 (17 self)
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DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a “snapshot ” of transcription levels within the cell. A major challenge in computational biology is to uncover, from such measurements, gene/protein interactions and key
Spacetime block codes from orthogonal designs
 IEEE Trans. Inform. Theory
, 1999
"... Abstract — We introduce space–time block coding, a new paradigm for communication over Rayleigh fading channels using multiple transmit antennas. Data is encoded using a space–time block code and the encoded data is split into � streams which are simultaneously transmitted using � transmit antennas. ..."
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Cited by 1524 (42 self)
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Abstract — We introduce space–time block coding, a new paradigm for communication over Rayleigh fading channels using multiple transmit antennas. Data is encoded using a space–time block code and the encoded data is split into � streams which are simultaneously transmitted using � transmit antennas
Capacity of a Mobile MultipleAntenna Communication Link in Rayleigh Flat Fading
"... We analyze a mobile wireless link comprising M transmitter and N receiver antennas operating in a Rayleigh flatfading environment. The propagation coefficients between every pair of transmitter and receiver antennas are statistically independent and unknown; they remain constant for a coherence int ..."
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Cited by 495 (22 self)
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interval of T symbol periods, after which they change to new independent values which they maintain for another T symbol periods, and so on. Computing the link capacity, associated with channel coding over multiple fading intervals, requires an optimization over the joint density of T M complex transmitted
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