Results 1  10
of
205
Comparison of metatranscriptomic samples based on ktuple 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

Cited by 4 (1 self)
 Add to MetaCart
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 alignmentbased sequence comparison methods cannot be used. Alignmentfree approaches based on ktuple
Loose Hamilton Cycles in Random kUniform Hypergraphs
, 2010
"... In the random hypergraph Hn,p;k each possible ktuple 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 ..."
Abstract

Cited by 2 (2 self)
 Add to MetaCart
In the random hypergraph Hn,p;k each possible ktuple 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 kuniform hypergraph H (k) n,p of order n, each possible ktuple 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 ..."
Abstract

Cited by 8 (4 self)
 Add to MetaCart
In the random kuniform hypergraph H (k) n,p of order n, each possible ktuple 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 kbest alignment
, 809
"... Optimal sequence alignments depend heavily on alignment scoring parameters. Given input sequences, parametric alignment is the wellstudied problem that asks for all possible optimal alignment summaries as parameters vary, as well as the optimality region of alignment scoring parameters which yield ..."
Abstract
 Add to MetaCart
each optimal alignment. But biologically correct alignments might be suboptimal for all parameter choices. Thus we extend parametric alignment to parametric kbest alignment, which asks for all possible ktuples of kbest alignment summaries (s1,s2,...,sk), as well as the kbest optimality region
Approximate listdecoding of direct product . . .
"... Given a message msg ∈ {0, 1} N, its kwise direct product encoding is the sequence of ktuples (msg(i1),..., msg(ik)) over all possible ktuples of indices (i1,..., ik) ∈ {1,..., N} k. We give an efficient randomized algorithm for approximate local listdecoding of direct product codes. That is, gi ..."
Abstract

Cited by 33 (8 self)
 Add to MetaCart
Given a message msg ∈ {0, 1} N, its kwise direct product encoding is the sequence of ktuples (msg(i1),..., msg(ik)) over all possible ktuples of indices (i1,..., ik) ∈ {1,..., N} k. We give an efficient randomized algorithm for approximate local listdecoding of direct product codes. That is
Noisetolerant learning, the parity problem, and the statistical query model
 J. ACM
"... We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise. This results in a polynomialtime 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 ..."
Abstract

Cited by 165 (2 self)
 Add to MetaCart
in the PAC model. In codingtheory 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 ktuple 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 ktuples for which all k decision trees are co ..."
Abstract

Cited by 28 (1 self)
 Add to MetaCart
the depth d restriction by "expected depth d", then this result fails. In the helpbit problem, we are permitted to ask k \Gamma 1 arbitrary binary questions about the ktuple of inputs. For each possible k \Gamma 1tuple of answers to these queries we will have a ktuple of decision trees
Topk query processing in uncertain databases
 In ICDE
, 2007
"... Topk processing in uncertain databases is semantically and computationally different from traditional topk processing. The interplay between score and uncertainty makes traditional techniques inapplicable. We introduce new probabilistic formulations for topk queries. Our formulations are based on ..."
Abstract

Cited by 125 (9 self)
 Add to MetaCart
on “marriage ” of traditional topk 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 dataintegration 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 ..."
Abstract

Cited by 109 (6 self)
 Add to MetaCart
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: bytable semantics
On matrices in prescribed conjugacy classes with no common invariant subspace and sum zero
 Duke Math. J
"... We determine those ktuples 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 DeligneSimpson problem. We deduce the result from earlier work of ours on preprojective algebras and ..."
Abstract

Cited by 37 (4 self)
 Add to MetaCart
We determine those ktuples 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 DeligneSimpson problem. We deduce the result from earlier work of ours on preprojective algebras
Results 1  10
of
205