2,782 research outputs found
On Security and Sparsity of Linear Classifiers for Adversarial Settings
Machine-learning techniques are widely used in security-related applications,
like spam and malware detection. However, in such settings, they have been
shown to be vulnerable to adversarial attacks, including the deliberate
manipulation of data at test time to evade detection. In this work, we focus on
the vulnerability of linear classifiers to evasion attacks. This can be
considered a relevant problem, as linear classifiers have been increasingly
used in embedded systems and mobile devices for their low processing time and
memory requirements. We exploit recent findings in robust optimization to
investigate the link between regularization and security of linear classifiers,
depending on the type of attack. We also analyze the relationship between the
sparsity of feature weights, which is desirable for reducing processing cost,
and the security of linear classifiers. We further propose a novel octagonal
regularizer that allows us to achieve a proper trade-off between them. Finally,
we empirically show how this regularizer can improve classifier security and
sparsity in real-world application examples including spam and malware
detection
Evolving rules for document classification
We describe a novel method for using Genetic Programming to create compact classification rules based on combinations of N-Grams (character strings). Genetic programs acquire fitness by producing rules that are effective classifiers in terms of precision and recall when evaluated against a set of training documents. We describe a set of functions and terminals and provide results from a classification task using the Reuters 21578 dataset. We also suggest that because the induced rules are meaningful to a human analyst they may have a number of other uses beyond classification and provide a basis for text mining applications
Leg ulcers in sickle cell disease.
Sickle cell disease is a single amino acid molecular disorder of hemoglobin leading to its pathological polymerization, red cell rigidity that causes poor microvascular blood flow, with consequent tissue ischemia and infarction. The manifestations of this disease are protean.Among them, leg ulcers represent a particularly disabling and chronic complication, often associated with a more severe clinical course.Despite the fact that this complication has been recognized since the early times of SCD, there has been little improvement in the efficacy of its management and clinical outcome over the past 100 years. Recently, vasculopathic abnormalities involving abnormal vascular tone and activated, adhesive endothelium have been recognized as another pathway to end organ damage in sickle cell disease. Vasculopathy of sickle cell disease has been implicated in the development of pulmonary hypertension, stroke, leg ulceration and priapism, particularly associated with hemolytic severity, and reported in other severe hemolytic disorders. The authors present the proceedings from the Educational Session on Chronic leg ulcers in Sickle cell disease, held during the 4th Annual Sickle Cell Disease Research and Educational Symposium, on February 17, 2010 in Fort Lauderdale, Fla
Clustering by genetic ancestry using genome-wide SNP data
<p>Abstract</p> <p>Background</p> <p>Population stratification can cause spurious associations in a genome-wide association study (GWAS), and occurs when differences in allele frequencies of single nucleotide polymorphisms (SNPs) are due to ancestral differences between cases and controls rather than the trait of interest. Principal components analysis (PCA) is the established approach to detect population substructure using genome-wide data and to adjust the genetic association for stratification by including the top principal components in the analysis. An alternative solution is genetic matching of cases and controls that requires, however, well defined population strata for appropriate selection of cases and controls.</p> <p>Results</p> <p>We developed a novel algorithm to cluster individuals into groups with similar ancestral backgrounds based on the principal components computed by PCA. We demonstrate the effectiveness of our algorithm in real and simulated data, and show that matching cases and controls using the clusters assigned by the algorithm substantially reduces population stratification bias. Through simulation we show that the power of our method is higher than adjustment for PCs in certain situations.</p> <p>Conclusions</p> <p>In addition to reducing population stratification bias and improving power, matching creates a clean dataset free of population stratification which can then be used to build prediction models without including variables to adjust for ancestry. The cluster assignments also allow for the estimation of genetic heterogeneity by examining cluster specific effects.</p
Cosmological entropy and generalized second law of thermodynamics in theory of gravity
We consider a spatially flat Friedmann-Lemaitre-Robertson-Walker space time
and investigate the second law and the generalized second law of thermodynamics
for apparent horizon in generalized modified Gauss Bonnet theory of gravity
(whose action contains a general function of Gauss Bonnet invariant and the
Ricci scalar: ). By assuming that the apparent horizon is in thermal
equilibrium with the matter inside it, conditions which must be satisfied by
are derived and elucidated through two examples: a quasi-de Sitter
space-time and a universe with power law expansion.Comment: 10 pages, minor changes, typos corrected, accepted for publication in
Europhysics Letter
An efficient k.p method for calculation of total energy and electronic density of states
An efficient method for calculating the electronic structure in large systems
with a fully converged BZ sampling is presented. The method is based on a
k.p-like approximation developed in the framework of the density functional
perturbation theory. The reliability and efficiency of the method are
demostrated in test calculations on Ar and Si supercells
Reaction intermediate rotation during the decarboxylation of coproheme to heme b in C. diphtheriae
Conserved Quantities in Gravity via Noether Symmetry
This paper is devoted to investigate gravity using Noether symmetry
approach. For this purpose, we consider Friedmann Robertson-Walker (FRW)
universe and spherically symmetric spacetimes. The Noether symmetry generators
are evaluated for some specific choice of models in the presence of
gauge term. Further, we calculate the corresponding conserved quantities in
each case. Moreover, the importance and stability criteria of these models are
discussed.Comment: 14 pages, accepted for publication in Chin. Phys. Let
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