188 research outputs found
Finding the Minimum-Weight k-Path
Given a weighted -vertex graph with integer edge-weights taken from a
range , we show that the minimum-weight simple path visiting
vertices can be found in time \tilde{O}(2^k \poly(k) M n^\omega) = O^*(2^k
M). If the weights are reals in , we provide a
-approximation which has a running time of \tilde{O}(2^k
\poly(k) n^\omega(\log\log M + 1/\varepsilon)). For the more general problem
of -tree, in which we wish to find a minimum-weight copy of a -node tree
in a given weighted graph , under the same restrictions on edge weights
respectively, we give an exact solution of running time \tilde{O}(2^k \poly(k)
M n^3) and a -approximate solution of running time
\tilde{O}(2^k \poly(k) n^3(\log\log M + 1/\varepsilon)). All of the above
algorithms are randomized with a polynomially-small error probability.Comment: To appear at WADS 201
External Sampling
36th International Colloquium, ICALP 2009, Rhodes, Greece, July 5-12, 2009, Proceedings, Part IWe initiate the study of sublinear-time algorithms in the external memory model [1]. In this model, the data is stored in blocks of a certain size B, and the algorithm is charged a unit cost for each block access. This model is well-studied, since it reflects the computational issues occurring when the (massive) input is stored on a disk. Since each block access operates on B data elements in parallel, many problems have external memory algorithms whose number of block accesses is only a small fraction (e.g. 1/B) of their main memory complexity.
However, to the best of our knowledge, no such reduction in complexity is known for any sublinear-time algorithm. One plausible explanation is that the vast majority of sublinear-time algorithms use random sampling and thus exhibit no locality of reference. This state of affairs is quite unfortunate, since both sublinear-time algorithms and the external memory model are important approaches to dealing with massive data sets, and ideally they should be combined to achieve best performance.
In this paper we show that such combination is indeed possible. In particular, we consider three well-studied problems: testing of distinctness, uniformity and identity of an empirical distribution induced by data. For these problems we show random-sampling-based algorithms whose number of block accesses is up to a factor of 1/âB smaller than the main memory complexity of those problems. We also show that this improvement is optimal for those problems.
Since these problems are natural primitives for a number of sampling-based algorithms for other problems, our tools improve the external memory complexity of other problems as well.David & Lucile Packard Foundation (Fellowship)Center for Massive Data Algorithmics (MADALGO)Marie Curie (International Reintegration Grant 231077)National Science Foundation (U.S.) (Grant 0514771)National Science Foundation (U.S.) (Grant 0728645)National Science Foundation (U.S.) (Grant 0732334)Symantec Research Labs (Research Fellowship
Level curvature distribution in a model of two uncoupled chaotic subsystems
We study distributions of eigenvalue curvatures for a block diagonal random matrix perturbed by
a full random matrix. The most natural physical realization of this model is a quantum chaotic system
with some inherent symmetry, such that its energy levels form two independent subsequences,
subject to a generic perturbation which does not respect the symmetry. We describe analytically
a crossover in the form of a curvature distribution with a tunable parameter namely the ratio of
inter/intra subsystem coupling strengths. We find that the peak value of the curvature distribution
is much more sensitive to the changes in this parameter than the power law tail behaviour. This
observation may help to clarify some qualitative features of the curvature distributions observed
experimentally in acoustic resonances of quartz blocks
Locally Decodable Codes for Edit Distance
Abstract. Locally decodable codes (LDC) [1,5] are error correcting codes that allow decoding (any) individual symbol of the message, by reading only few symbols of the codeword. Consider an application such as storage solutions for large data, where errors may occur in the disks (or some disks may just crush). In such an application, it is often de-sirable to recover only small portions of the data (have random access). Thus, in such applications, using LDC provides enormous efficiency gains over standard error correcting codes (ECCs), that need to read the en-tire encoded message to learn even a single bit of information. Typically, LDCâs, as well as standard ECCâs decode the encoded messaged if upto some bounded fraction of the symbols had been modified. This corre-sponds to decoding strings of bounded Hamming distance from a valid codeword. An often more realistic metric is the edit distance, measur-ing the shortest sequence of insertions and deletions (indel.) of symbols leading from one word to another. For example, (few) indel. modifica
On the critical level-curvature distribution
The parametric motion of energy levels for non-interacting electrons at the
Anderson localization critical point is studied by computing the energy
level-curvatures for a quasiperiodic ring with twisted boundary conditions. We
find a critical distribution which has the universal random matrix theory form
for large level-curvatures corresponding to
quantum diffusion, although overall it is close to approximate log-normal
statistics corresponding to localization. The obtained hybrid distribution
resembles the critical distribution of the disordered Anderson model and makes
a connection to recent experimental data.Comment: 4 pages, 3 figure
A preferential attachment model with random initial degrees
In this paper, a random graph process is studied and its
degree sequence is analyzed. Let be an i.i.d. sequence. The
graph process is defined so that, at each integer time , a new vertex, with
edges attached to it, is added to the graph. The new edges added at time
t are then preferentially connected to older vertices, i.e., conditionally on
, the probability that a given edge is connected to vertex i is
proportional to , where is the degree of vertex
at time , independently of the other edges. The main result is that the
asymptotical degree sequence for this process is a power law with exponent
, where is the power-law exponent
of the initial degrees and the exponent predicted
by pure preferential attachment. This result extends previous work by Cooper
and Frieze, which is surveyed.Comment: In the published form of the paper, the proof of Proposition 2.1 is
incomplete. This version contains the complete proo
An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis
Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is
a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a
complex disease caused by metastasis of tumor cells from their primary site and
is characterized by intricate interplay of molecular interactions.
Identification of targets for multifactorial diseases such as SBC, the most
frequent complication of breast and prostate cancers, is a challenge. Towards
achieving our aim of identification of targets specific to SBC, we constructed
a 'Cancer Genes Network', a representative protein interactome of cancer genes.
Using graph theoretical methods, we obtained a set of key genes that are
relevant for generic mechanisms of cancers and have a role in biological
essentiality. We also compiled a curated dataset of 391 SBC genes from
published literature which serves as a basis of ontological correlates of
secondary bone cancer. Building on these results, we implement a strategy based
on generic cancer genes, SBC genes and gene ontology enrichment method, to
obtain a set of targets that are specific to bone metastasis. Through this
study, we present an approach for probing one of the major complications in
cancers, namely, metastasis. The results on genes that play generic roles in
cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have
broader implications in understanding the role of molecular regulators in
mechanisms of cancers. Specifically, our study provides a set of potential
targets that are of ontological and regulatory relevance to secondary bone
cancer.Comment: 54 pages (19 pages main text; 11 Figures; 26 pages of supplementary
information). Revised after critical reviews. Accepted for Publication in
PLoS ON
Erratum to the âUse of pleural fluid C-reactive protein in diagnosis of pleural effusionsâ [Respiratory medicine 94(5) 432â435]
Dipyrone in association with atropine inhibits the effect on gastric emptying induced by hypoglycemia in rats
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