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Results 1 - 10
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205
Comparison of metatranscriptomic samples based on k-tuple frequencies. PLoS One
"... Background: The comparison of samples, or beta diversity, is one of the essential problems in ecological studies. Next generation sequencing (NGS) technologies make it possible to obtain large amounts of metagenomic and metatranscriptomic short read sequences across many microbial communities. De no ..."
Abstract
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Cited by 4 (1 self)
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novo assembly of the short reads can be especially challenging because the number of genomes and their sequences are generally unknown and the coverage of each genome can be very low, where the traditional alignment-based sequence comparison methods cannot be used. Alignment-free approaches based on k-tuple
Loose Hamilton Cycles in Random k-Uniform Hypergraphs
, 2010
"... In the random hypergraph Hn,p;k each possible k-tuple appears independently with probability p. A loose Hamilton cycle is a cycle in which every pair of adjacent edges intersects in a single vertex. We prove that if pn k−1 / log n tends to infinity with n then lim Pr(Hn,p;k contains a loose Hamilton ..."
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Cited by 2 (2 self)
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In the random hypergraph Hn,p;k each possible k-tuple appears independently with probability p. A loose Hamilton cycle is a cycle in which every pair of adjacent edges intersects in a single vertex. We prove that if pn k−1 / log n tends to infinity with n then lim Pr(Hn,p;k contains a loose
Optimal divisibility conditions for loose Hamilton cycles in random hypergraphs
- ELECTRON. J. COMBIN
, 2012
"... In the random k-uniform hypergraph H (k) n,p of order n, each possible k-tuple appears independently with probability p. A loose Hamilton cycle is a cycle of order n in which every pair of consecutive edges intersects in a single vertex. It was shown by Frieze that if p> c(log n)/n2 for some abso ..."
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Cited by 8 (4 self)
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In the random k-uniform hypergraph H (k) n,p of order n, each possible k-tuple appears independently with probability p. A loose Hamilton cycle is a cycle of order n in which every pair of consecutive edges intersects in a single vertex. It was shown by Frieze that if p> c(log n)/n2 for some
Parametric k-best alignment
, 809
"... Optimal sequence alignments depend heavily on alignment scoring parameters. Given input sequences, parametric alignment is the well-studied problem that asks for all possible optimal alignment summaries as parameters vary, as well as the optimality region of alignment scoring parameters which yield ..."
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each optimal alignment. But biologically correct alignments might be suboptimal for all parameter choices. Thus we extend parametric alignment to parametric k-best alignment, which asks for all possible k-tuples of k-best alignment summaries (s1,s2,...,sk), as well as the k-best optimality region
Approximate list-decoding of direct product . . .
"... Given a message msg ∈ {0, 1} N, its k-wise direct product encoding is the sequence of k-tuples (msg(i1),..., msg(ik)) over all possible k-tuples of indices (i1,..., ik) ∈ {1,..., N} k. We give an efficient randomized algorithm for approximate local list-decoding of direct product codes. That is, gi ..."
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Cited by 33 (8 self)
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Given a message msg ∈ {0, 1} N, its k-wise direct product encoding is the sequence of k-tuples (msg(i1),..., msg(ik)) over all possible k-tuples of indices (i1,..., ik) ∈ {1,..., N} k. We give an efficient randomized algorithm for approximate local list-decoding of direct product codes. That is
Noise-tolerant learning, the parity problem, and the statistical query model
- J. ACM
"... We describe a slightly sub-exponential time algorithm for learning parity functions in the presence of random classification noise. This results in a polynomial-time algorithm for the case of parity functions that depend on only the first O(log n log log n) bits of input. This is the first known ins ..."
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Cited by 165 (2 self)
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in the PAC model. In coding-theory terms, what we give is a poly(n)-time algorithm for decoding linear k × n codes in the presence of random noise for the case of k = clog n log log n for some c> 0. (The case of k--- O(log n) is trivial since one can just individually check each of the 2 k possible
Products and Help Bits in Decision Trees
, 1994
"... We investigate two problems concerning the complexity of evaluating a function f at a k-tuple of unrelated inputs by k parallel decision tree algorithms. In the product problem, for some fixed depth bound d, we seek to maximize the fraction of input k-tuples for which all k decision trees are co ..."
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Cited by 28 (1 self)
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the depth d restriction by "expected depth d", then this result fails. In the help-bit problem, we are permitted to ask k \Gamma 1 arbitrary binary questions about the k-tuple of inputs. For each possible k \Gamma 1-tuple of answers to these queries we will have a k-tuple of decision trees
Top-k query processing in uncertain databases
- In ICDE
, 2007
"... Top-k processing in uncertain databases is semantically and computationally different from traditional top-k processing. The interplay between score and uncertainty makes traditional techniques inapplicable. We introduce new probabilistic formulations for top-k queries. Our formulations are based on ..."
Abstract
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Cited by 125 (9 self)
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on “marriage ” of traditional top-k semantics and possible worlds semantics. In the light of these formulations, we construct a framework that encapsulates a state space model and efficient query processing techniques to tackle the challenges of uncertain data settings. We prove that our techniques are optimal
Data integration with uncertainty.
- In Proc. of VLDB,
, 2007
"... Abstract This paper reports our first set of results on managing uncertainty in data integration. We posit that data-integration systems need to handle uncertainty at three levels, and do so in a principled fashion. First, the semantic mappings between the data sources and the mediated schema may b ..."
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Cited by 109 (6 self)
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be extracted using information extraction techniques and so may yield erroneous data. As a first step to building such a system, we introduce the concept of probabilistic schema mappings and analyze their formal foundations. We show that there are two possible semantics for such mappings: by-table semantics
On matrices in prescribed conjugacy classes with no common invariant subspace and sum zero
- Duke Math. J
"... We determine those k-tuples of conjugacy classes of matrices from which it is possible to choose matrices that have no common invariant subspace and have sum zero. This is an additive version of the Deligne-Simpson problem. We deduce the result from earlier work of ours on preprojective algebras and ..."
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Cited by 37 (4 self)
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We determine those k-tuples of conjugacy classes of matrices from which it is possible to choose matrices that have no common invariant subspace and have sum zero. This is an additive version of the Deligne-Simpson problem. We deduce the result from earlier work of ours on preprojective algebras
Results 1 - 10
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205
