Martos Torreblanca, Alberto(Universitat Politècnica de València, 2012-10-03)
La motivación principal de este proyecto es aportar el uso de una tecnología
Open Source que realice las mismas funciones que la herramienta propietaria y
que proporcione otras funcionalidades adicionales que supongan ...
We describe a systematic approach called reframing, defined as the process of preparing a machine learning model (e.g., a classifier) to perform well over a range of operating contexts. One way to achieve this is by ...
[EN] The widespread use of experimental benchmarks in AI research has created competition and collaboration dynamics that are still poorly understood. Here we provide an innovative methodology to explore these dynamics and ...
Benacloch Ayuso, José Luis(Universitat Politècnica de València, 2012-04-10)
Este proyecto consiste en la creación de una plataforma, denominada RL-GGP (Reinforcement Learning General Game Playing), que permita usar y evaluar algoritmos de aprendizaje por refuerzo en diferentes tipos de juegos por ...
Receiver Operating Characteristic (ROC) analysis is one of the most popular tools for the visual assessment and understanding of classifier performance. In this paper we present a new representation of regression models ...
ROC curves and cost curves are two popular ways of visualising classifier performance, finding appropriate thresholds according to the operating condition, and deriving useful aggregated measures such as the area under the ...
Meseguer Herrero, Sergio(Universitat Politècnica de València, 2021-10-15)
[ES] Actualmente, nos encontramos ante una etapa con una relevancia crucial en el ámbito de la inteligencia artificial (IA). Esta etapa está marcada por un cambio en la forma que los humanos realizan tareas, ya que cada ...
[EN] The quality of the decisions made by a machine learning model depends on the data and the operating conditions during deployment. Often, operating conditions such as class distribution and misclassification costs have ...
Iturbide Griñán, Sara(Universitat Politècnica de València, 2022-10-18)
[CA] En l'actualitat, part de la població pateix problemes de lectura la qual cosa obri la porta a la necessitat de facilitar mecanismes per a la simplificació de textos fins a una versió de lectura fàcil que permeta a la ...
Zhou, Lexin(Universitat Politècnica de València, 2023-06-20)
[EN] Pretrained artificial intelligence models are made more human-like and human-aligned by scaling them up in resources (e.g., by increasing compute, training data and parameter size) and shaping them up with human ...
Hernández Orallo, José(Springer International Publishing, 2015)
We establish a setting for asynchronous stochastic tasks that
account for episodes, rewards and responses, and, most especially, the
computational complexity of the algorithm behind an agent solving a
task. This is used ...
[EN] The current analysis in the AI safety literature usually combines a risk or safety issue (e.g., interruptibility) with a particular paradigm for an AI agent (e.g., reinforcement learning).
However, there is currently ...
[EN] Modern machine learning systems are still lacking in the kind of general intelligence
and common sense reasoning found, not only in humans, but across the animal kingdom.
Many animals are capable of solving seemingly ...
Telle, Jan Arne; Hernández-Orallo, José; Ferri Ramírez, César(Springer-Verlag, 2019-09)
[EN] The theoretical hardness of machine teaching has usually been analyzed for a range of concept languages under several variants of the teaching dimension: the minimum number of examples that a teacher needs to figure ...
Insa Cabrera, Javier(Universitat Politècnica de València, 2016-06-17)
[EN] Under the view of artificial intelligence, an intelligent agent is an autonomous entity which interacts in an environment through observations and actions, trying to achieve one or more goals with the aid of several ...
Contreras Ochando, Lidia(Universitat Politècnica de València, 2021-02-04)
[ES] El proceso de ciencia de datos es esencial para extraer valor de los datos. Sin embargo, la parte más tediosa del proceso, la preparación de los datos, implica una serie de formateos, limpieza e identificación de ...
Martínez-Plumed, Fernando; Hernández-Orallo, José(Institute of Electrical and Electronics Engineers, 2023-08)
[EN] The concepts of innovation, creativity, problem solving, effective communication, autonomy and critical thinking are at the core of becoming a good data scientist. Adapting to new technological resources and tools is ...
[EN] The progress of some AI paradigms such as deep learning is said to be linked to an exponential growth in the number of parameters. There are many studies corroborating these trends, but does this translate into an ...
[EN] In the last 20 years the Turing test has been left further behind by new developments in artificial intelligence. At the same time, however, these developments have revived some key elements of the Turing test: imitation ...