Browsing Data Science (DS) by Title
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Natureinspired approaches for distance metric learning in multivariate time series classification
(IEEE Congress on Evolutionary Computation (CEC), 201707)The applicability of time series data mining in many different fields has motivated the scientific community to focus on the development of new methods towards improving the performance of the classifiers over this particular ... 
Natureinspired approaches for distance metric learning in multivariate time series classification
(IEEE Congress on Evolutionary Computation, 2017)The applicability of time series data mining in many different fields has motivated the scientific community to focus on the development of new methods towards improving the performance of the classifiers over this particular ... 
Natureinspired heuristics for the multiplevehicle selective pickup and delivery problem under maximum profit and incentive fairness criteria
(IEEE Congress on Evolutionary Computation, 2017)This work focuses on widescale freight transportation logistics motivated by the sharp increase of online shopping stores and the upsurge of Internet as the most frequently utilized selling channel during the last decade. ... 
Nearlyoptimal scheduling of users with Markovian timevarying transmission rates
(Performance Evaluation, 20160101)We address the problem of developing a wellperforming and implementable scheduler of users with wireless connections to the central controller, which arise in areas such as mobile data networks, heterogeneous networks, ... 
A new approach to categorize continuous variables in prediction models: Proposal and validation
(Statistical Methods in Medical Research, 201712)When developing prediction models for application in clinical practice, health practitioners usually categorise clinical variables that are continuous in nature. Although categorisation is not regarded as advisable from ... 
A note on Poisson goodnessoffit tests for ionizing radiation induced chromosomal aberration samples
(International Journal of Radiation Biology, 20180613)Purpose: To present Poisson exact goodnessoffit tests as alternatives and complements to the asymptotic utest, which is the most widely used in cytogenetic biodosimetry, to decide whether a sample of chromosomal aberrations ... 
A note on the behavior of majority voting in multiclass domains with biased annotators
(IEEE Transactions on Knowledge and Data Engineering, 201805)Majority voting is a popular and robust strategy to aggregate different opinions in learning from crowds, where each worker labels examples ac cording to their own criteria. Although it has been extensively studied in the ... 
A note on the Boltzmann distribution and the linear ordering problem
(Lecture Notes in Computer Science, 20161001)The Boltzmann distribution plays a key role in the field of optimization as it directly connects this field with that of probability. Basically, given a function to optimize, the Boltzmann distribution associated to this ... 
A novel adaptive densitybased ACO algorithm with minimal encoding redundancy for clustering problems
(2016 IEEE Congress on Evolutionary Computation, CEC 2016, 20161114)In the socalled Big Data paradigm descriptive analytics are widely conceived as techniques and models aimed at discovering knowledge within unlabeled datasets (e.g. patterns, similarities, etc) of utmost help for subsequent ... 
A novel Fireworks Algorithm with wind inertia dynamics and its application to traffic forecasting
(IEEE Congress on Evolutionary Computation, 2017)Fireworks Algorithm (FWA) is a recently contributed heuristic optimization method that has shown a promising performance in applications stemming from different domains. Improvements to the original algorithm have been ... 
On the applicability of ant colony optimization to nonintrusive load monitoring in smart grids
(Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 20151231)Along with the proliferation of the Smart Grid, power load disaggregation is a research area that is lately gaining a lot of popularity due to the interest of energy distribution companies and customers in identifying ... 
On the estimation of variance parameters in nonstandard generalised linear mixed models: Application to penalised smoothing
(Statistics and Computing, 20180124)We present a novel method for the estimation of variance parameters in generalised linear mixed models. The method has its roots in Harville (1977)'s work, but it is able to deal with models that have a precision matrix ... 
On the evaluation and selection of classifier learning algorithms with crowdsourced data
(Applied Soft Computing, 20190216)In many current problems, the actual class of the instances, the ground truth, is unavail able. Instead, with the intention of learning a model, the labels can be crowdsourced by harvesting them from different annotators. ... 
On the Gittins index in the M/G/1 queue
(Queueing Systems, 20091231)For an M/G/1 queue with the objective of minimizing the mean number of jobs in the system, the Gittins index rule is known to be optimal among the set of nonanticipating policies. We develop properties of the Gittins ... 
On the relevance of preprocessing in predictive maintenance for dynamic systems
(Predictive Maintenance in Dynamic Systems, 2018)The complexity involved in the process of realtime datadriven monitoring dynamic systems for predicted maintenance is usually huge. With more or less indepth any datadriven approach is sensitive to data preprocessing, ... 
OnLine Dynamic Time Warping for Streaming Time Series
(Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2017. Lecture Notes in Computer Science, 201709)Dynamic Time Warping is a wellknown measure of dissimilarity between time series. Due to its flexibility to deal with nonlinear distortions along the time axis, this measure has been widely utilized in machine learning ... 
Online Elastic Similarity Measures for time series
(Pattern Recognition, 201904)The way similarity is measured among time series is of paramount importance in many data mining and machine learning tasks. For instance, Elastic Similarity Measures are widely used to determine whether two time series are ... 
Opportunistic schedulers for optimal scheduling of flows in wireless systems with ARQ feedback
(Final Program  2012 24th International Teletraffic Congress, ITC 24, 20121231)In this paper we study three opportunistic schedulers for the problem of optimal multiclass flowlevel scheduling in wireless downlink and uplink systems. For user channels we employ the GilbertElliot model of good and ... 
Optimal anticipative congestion control of flows with timevarying input stream
(Performance Evaluation, 20121231)This paper is concerned with a new type of congestion control method that we call anticipative congestion control, which exploits probabilistic information available at a network node about congestion at other nodes. ... 
Optimal congestion control of TCP flows for internet routers
(Performance Evaluation Review, 20121231)In this work we address the problem of fast and fair transmission of flows in a router, which is a fundamental issue in networks like the Internet. We model the interaction between a TCP source and a bottleneck queue with ...