learning algorithms
Online machine learning algorithms to predict link quality in community wireless mesh networks
... predictions for links when it is their first day of activity or if they have been active for a very short time in the previous days. However, we circumvented this problem by using the baseline to generate predictions in ...
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The use of machine learning algorithms for the study of business profitability : a new approach based on preferences
... The use of an approach based on preferences has provided good results in other fields (see, e.g., Herbrich et al., 1999, for an application to the modelling of consumers’ behavior). In the present paper, we test the ...
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Analysis and implementation of deep learning algorithms for face to face translation based on audio-visual representations
... saved correspond to the last epoch of training (400). Since every single value of the losses for every video has been saved, the number of iterations amounts to a high number, so it has been decided to average the values ...
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Analysis and implementation of multiagent deep reinforcement learning algorithms for natural disaster monitoring with swarms of drones
... Reinforcement Learning (RL) is learning what to do—how to map situations to actions— so as to maximize a numerical reward signal ...RL algorithms offer ways to obtain optimal policies π for problems ...
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Automated Analysis of Source Code Patches using Machine Learning Algorithms
... machine learning in the tool, to incorporate information retrieved from developers´ discussion forums, and to integrate the tool with other databases dealing with vulnerability reports and security ...
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An Indoor Positioning System Based on Wearables for Ambient Assisted Living
... In this paper, we have presented an indoor WiFi fingerprinting positioning system based on wearable devices and Machine Learning algorithms. The system is robust, reliable, secure and unobtrusive, ...
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TítuloA Review on IoT Deep Learning UAV Systems for Autonomous Obstacle Detection and Collision Avoidance
... the learning paradigm, Reinforcement Learning (RL) algorithms [56] have been widely used in robotic ...supervised learning algorithms that are based on learning through ...The ...
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Identification of Pronunciation Errors in L2 English Speech by Spanish Speaking Natives for S Impure Sounds
... Language Learning (CALL) systems in the 1960s [53], taking the first approach in the medi- cal field for automatic display and detection for the deaf and hard of hearing in Children ...Supervised Learning ...
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Clustering based feature learning on variable stars
... Machine Learning is a field in computer science which aims to develop algorithms and models that can learn from and make predictions on ...machine learning algorithms use models which are ...
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App reviews analysis with machine learning
... Machine Learning it is now possible to categorize large amounts of data with a small manually labeled ...Machine Learning algorithms on the labeling, as well as auto- matically classifying the ...
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Cellular memetic algorithms
... the algorithms used, and a comparison of our results versus those of other well-known algorithms in the ...studied algorithms, in- cluding three simple heuristics (GRAD, Simulated Annealing –SA– and ...
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To Innovate or not to Innovate in the Didactic Second Language Scenario (and How) – that Is the Question?
... Following this same line, Castaño, Maíz and Garay bring into focus in the sixth article two research tendencies in the near future classified according to pedagogical, technological and crucial criteria: the concern ...
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TítuloNet net Auto machine learning (AutoML) prediction of complex ecosystems
... tion about all these collections of nodes and links is so large that it is impossible for a single person to remember and rationalize all possible connections in known networks. Consequently, it is even more difficult to ...
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Experiencia y recursos para mejorar la docencia en la Universidad
... En los planes de estudio se hace más hincapié en aspectos intelectuales (latín, física, gramática) en lugar de aspectos humanos como relaciones interpersonales (pareja, hijos, amigos, compañeros), comunicación, gestión ...
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Learning Tractable Bayesian Networks
... One of the main advantages of BNs is that, as generative models, they can answer all condi- tional probability queries involving the variables of the network. In supervised classification, if the value of a certain set ...
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Virtual player design using self-learning via competitive coevolutionary algorithms
... (CC) algorithms for the automatic generation of winning game strategies in Planet Wars, the RTS game associated with the 2010 ...proposed algorithms is described and a statistical analysis of the results is ...
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An investigation on automatic systems for fault diagnosis in chemical processes
... An important issue to face is to standardize the different methods that could be used for the same purpose in terms of their final performance by an unique diagnosis index. The use of a single index would allow selecting ...
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OPPOSITE LEARNING STRATEGIES FOR IMPROVING THE SEARCH PROCESS OF ANT-BASED ALGORITHMS
... tions. Boxplots, statistical analysis and fitness-distance plots confirm that the use of our strategy allows AK to reach different complete instantiations, in terms of quality and structure. The infor- mation provided by ...
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Study and development of reinforcement learning multiagent collaborative algorithms for solving families of problems
... distributed algorithms output the policies and a value functions that multiple agents have agreed ...transfer learning known as starting-point methods, as explained in Section ...
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