Machine Learning: Recent submissions
Now showing items 120 of 67

An adaptive neuroevolutionbasedhyperheuristic
(The Genetic and Evolutionary Computation Conference, 20200708)According to the NoFreeLunch theorem, an algorithm that performs efficiently on any type of problem does not exist. In this sense, algorithms that exploit problemspecific knowledge usually outperform more generic ... 
Optimization of deep learning precipitation models using categorical binary metrics
(Journal of Advances in Modeling Earth Systems, 2020)This work introduces a methodology for optimizing neural network models using a combination of continuous and categorical binary indices in the context of precipitation forecasting. Probability of detection or false alarm ... 
An efficient Kmeans clustering algorithm for tall data
(DATA MINING AND KNOWLEDGE DISCOVERY, 2020)The analysis of continously larger datasets is a task of major importance in a wide variety of scientific fields. Therefore, the development of efficient and parallel algorithms to perform such an analysis is a a crucial ... 
Supervised nonparametric discretization based on Kernel density estimation
(Pattern Recognition Letters, 20191219)Nowadays, machine learning algorithms can be found in many applications where the classifiers play a key role. In this context, discretizing continuous attributes is a common step previous to classification tasks, the main ... 
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 ... 
An Experimental Study in Adaptive Kernel Selection for Bayesian Optimization
(IEEE Access, 2019)Bayesian Optimization has been widely used along with Gaussian Processes for solving expensivetoevaluate blackbox optimization problems. Overall, this approach has shown good results, and particularly for parameter ... 
Hybrid Heuristics for the Linear Ordering Problem
(2019 IEEE Congress on Evolutionary Computation, CEC 2019  Proceedings, 2019)The linear ordering problem (LOP) is one of the classical NPHard combinatorial optimization problems. Motivated by the difficulty of solving it up to optimality, in recent decades a great number of heuristic and metaheuristic ... 
Soft information for localizationofthings
(Proceeding of the IEEE, 20191101)Location awareness is vital for emerging Internetof Things applications and opens a new era for Localizationof Things. This paper first reviews the classical localization techniques based on singlevalue metrics, such ... 
Data generation approaches for topic classification in multilingual spoken dialog systems
(ACM International Conference Proceeding Series, 2019)The conception of spokendialog systems (SDS) usually faces the problem of extending or adapting the system to multiple languages. This implies the creation of modules specically for the new languages, which is a time ... 
Anatomy of the attraction basins: Breaking with the intuition
(Evolutionary Computation, 2019)olving combinatorial optimization problems efficiently requires the development of algorithms that consider the specific properties of the problems. In this sense, local search algorithms are designed over a neighborhood ... 
Characterising the rankings produced by combinatorial optimisation problems and finding their intersections
(GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference, 2019)The aim of this paper is to introduce the concept of intersection between combinatorial optimisation problems. We take into account that most algorithms, in their machinery, do not consider the exact objective function ... 
Approaching the Quadratic Assignment Problem with Kernels of Mallows Models under the Hamming Distance
(Proceedings of the Genetic and Evolutionary Computation Conference Companion, 201907)The Quadratic Assignment Problem (QAP) is a specially challenging permutationbased nphard combinatorial optimization problem, since instances of size $n>40$ are seldom solved using exact methods. In this sense, many ... 
Sentiment analysis with genetically evolved Gaussian kernels
(GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference, 2019)Sentiment analysis consists of evaluating opinions or statements based on text analysis. Among the methods used to estimate the degree to which a text expresses a certain sentiment are those based on Gaussian Processes. ... 
Optimal multiimpulse space rendezvous considering limited impulse using a discretized Lambert problem combined with evolutionary algorithms
(8th European Conference for Aeronautics and Space Sciences, 20190701)In this paper, a direct approach is presented to tackle the multiimpulse rendezvous problem considering the impulse limit. Particularly, the standard Lambert problem is extended toward several consequential orbit transfers ... 
An evolutionary discretized Lambert approach for optimal longrange rendezvous considering impulse limit
(Aerospace Science and Technology, 20190918)In this paper, an approach is presented for finding the optimal longrange space rendezvous in terms of fuel and time, considering limited impulse. In this approach , the Lambert problem is expanded towards a discretized ... 
Analyzing rare event, anomaly, novelty and outlier detection terms under the supervised classification framework
(Artificial Intelligence Review, 20190901)In recent years, a variety of research areas have contributed to a set of related problems with rare event, anomaly, novelty and outlier detection terms as the main actors. These multiple research areas have created a ... 
CrowdCentric Counting via Unsupervised Learning
(2019 IEEE International Conference on Communications Workshops (ICC Workshops), 20190711)Counting targets (people or things) within a monitored area is an important task in emerging wireless applications,including those for smart environments, safety, and security.Conventional devicefree radiobased ... 
A mathematical analysis of edas with distancebased exponential models
(GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference Companion, 20190701)Estimation of Distribution Algorithms have been successfully used for solving many combinatorial optimization problems. One type of problems in which Estimation of Distribution Algorithms have presented strong competitive ... 
Belief Condensation Filtering For RssiBased State Estimation In Indoor Localization
(2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019)Recent advancements in signal processing and communication systems have resulted in evolution of an intriguing concept referred to as Internet of Things (IoT). By embracing the IoT evolution, there has been a surge of ... 
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. ...