Search results for "ALGORITHM"

Scaling Up a Metric Learning Algorithm for Image Recognition and Representation

2008

Maximally Collapsing Metric Learning is a recently proposed algorithm to estimate a metric matrix from labelled data. The purpose of this work is to extend this approach by considering a set of landmark points which can in principle reduce the cost per iteration in one order of magnitude. The proposal is in fact a generalized version of the original algorithm that can be applied to larger amounts of higher dimensional data. Exhaustive experimentation shows that very similar behavior at a lower cost is obtained for a wide range of the number of landmark points used.

The Three Steps of Clustering In The Post-Genomic Era

2013

This chapter descibes the basic algorithmic components that are involved in clustering, with particular attention to classification of microarray data.

Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs

2014

We develop an algorithm that incorporates network information into regression settings. It simultaneously estimates the covariate coefficients and the signs of the network connections (i.e. whether the connections are of an activating or of a repressing type). For the coefficient estimation steps an additional penalty is set on top of the lasso penalty, similarly to Li and Li (2008). We develop a fast implementation for the new method based on coordinate descent. Furthermore, we show how the new methods can be applied to time-to-event data. The new method yields good results in simulation studies concerning sensitivity and specificity of non-zero covariate coefficients, estimation of networ…

Incrementally Assessing Cluster Tendencies with a~Maximum Variance Cluster Algorithm

2003

A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the benefits of the plain clustering algorithm with regard to other approaches for clustering. Experiments using both synthetic and real data have been performed in order to evaluate the differences between the proposed methodology and the plain use of the Maximum Variance algorithm. According to the results obtained, the proposal constitutes an efficient and accurate alternative.

Calcification is not the Achilles' heel of cold-water corals in an acidifying ocean

2015

Ocean acidification is thought to be a major threat to coral reefs: laboratory evidence and CO2 seep research has shown adverse effects on many coral species, although a few are resilient. There are concerns that cold-water corals are even more vulnerable as they live in areas where aragonite saturation (?ara) is lower than in the tropics and is falling rapidly due to CO2 emissions. Here, we provide laboratory evidence that net (gross calcification minus dissolution) and gross calcification rates of three common cold-water corals, Caryophyllia smithii, Dendrophyllia cornigera, and Desmophyllum dianthus, are not affected by pCO2 levels expected for 2100 (pCO2 1058 ?atm, ?ara 1.29), and nor a…

Genome-wide detection of signatures of selection in three Valdostana cattle populations

2020

International audience; The Valdostana is a local dual purpose cattle breed developed in Italy. Three populations are recognized within this breed, based on coat colour, production level, morphology and temperament: Valdostana Red Pied (VPR), Valdostana Black Pied (VPN) and Valdostana Chestnut (VCA). Here, we investigated putative genomic regions under selection among these three populations using the Bovine 50K SNP array by combining three different statistical methods based either on allele frequencies (F-ST) or extended haplotype homozygosity (iHS and Rsb). In total, 8, 5 and 8 chromosomes harbouring 13, 13 and 16 genomic regions potentially under selection were identified by at least tw…

Neural networks with non-uniform embedding and explicit validation phase to assess Granger causality

2015

A challenging problem when studying a dynamical system is to find the interdependencies among its individual components. Several algorithms have been proposed to detect directed dynamical influences between time series. Two of the most used approaches are a model-free one (transfer entropy) and a model-based one (Granger causality). Several pitfalls are related to the presence or absence of assumptions in modeling the relevant features of the data. We tried to overcome those pitfalls using a neural network approach in which a model is built without any a priori assumptions. In this sense this method can be seen as a bridge between model-free and model-based approaches. The experiments perfo…

Distributed Pseudo-Gossip Algorithm and Finite-Length Computational Codes for Efficient In-Network Subspace Projection

2013

In this paper, we design a practical power-efficient algorithm for Wireless Sensor Networks (WSN) in order to obtain, in a distributed manner, the projection of an observed sampled spatial field on a subspace of lower dimension. This is an important problem that is motivated in various applications where there are well defined subspaces of interest (e.g., spectral maps in cognitive radios). As opposed to traditional Gossip Algorithms used for subspace projection, where separation of channel coding and computation is assumed, our algorithm combines binary finite-length Computational Coding and a novel gossip-like protocol with certain communication rules, achieving important savings in conve…

Decision Making in Evolving Artificial Systems

2001

The theme of this workshop is artificial perception. In this chapter we will argue that the ecological function of perception is to serve decision-making. If this is so the mechanisms chosen to implement perception, in natural or artificial systems, will be constrained by the requirements of decision-making and theories of decision-making will inevitably influence theories of perception. In what follows we will look at decision-making from what we hope is a new perspective, applying concepts and techniques developed by what we will call “new artificial intelligence”. We will begin, in the second part of the chapter, with a review of traditional, “normative” theories of decision-making and o…

1993

Genetics and developmental genetics have given us such a wealth of new insight that, at the end of this century, the synthetic theory can no longer be maintained in the strict “orthodox” sense in which it was started.