Dowe, David L.; Hernández Orallo, José(Elsevier, 2012-04)
[EN] Complex, but specific, tasks¿such as chess or Jeopardy!¿are popularly seen as milestones for artificial intelligence (AI). However, they are not appropriate for evaluating the intelligence of machines or measuring the ...
[EN] AI systems are usually evaluated on a range of problem instances and compared to other AI systems that use different strategies. These instances are rarely independent. Machine learning, and supervised learning in ...
Martínez Plumed, Fernando; Ferri Ramírez, César; Hernández Orallo, José; Ramírez Quintana, María José(SAGE Publications (UK and US), 2015-10)
Identifying the balance between remembering and forgetting is the key to abstraction
in the human brain and, therefore, the creation of memories and knowledge. We
present an incremental, lifelong view of knowledge ...
[EN] A common way of learning to perform a task is to observe how it is carried out by experts. However, it is well known that for most tasks there is no unique way to perform them. This is especially noticeable the more ...
In this paper, we push forward the idea of machine learning
systems for which the operators can be modi ed and netuned for each
problem. This allows us to propose a learning paradigm where users can
write (or adapt) ...
[EN] In this paper we develop a framework for analysing the impact of Artificial Intelligence (AI) on
occupations. This framework maps 59 generic tasks from worker surveys and an occupational
database to 14 cognitive ...
[EN] Nowadays, there is an increasing concern in machine learning about the causes underlying unfair decision making, that is, algorithmic decisions discriminating some groups over others, especially with groups that are ...
Bella Sanjuán, Antonio(Universitat Politècnica de València, 2012-07-31)
El aprendizaje autom�atico es un �area de investigaci�on que proporciona algoritmos
y t�ecnicas que son capaces de aprender autom�aticamente a partir
de experiencias pasadas. Estas t�ecnicas son esenciales en el �area de ...
Maguedong Djoumessi, Celestine Periale(Universitat Politècnica de València, 2014-11-24)
[EN] Many solutions to cost-sensitive classification (and regression) rely on some or all of the following
assumptions: we have complete knowledge about the cost context at training time, we
can easily re-train whenever ...
Romero Alvarado, Daniel(Universitat Politècnica de València, 2023-09-19)
[ES] Los grandes modelos de lenguaje natural suelen ser entrenados con datasets pretratados y
limpiados de impurezas como faltas de ortografía, contracciones, etc. Por lo tanto, existe una
diferencia entre los datos de ...
Multidimensional data is systematically analysed at multiple granularities by applying aggregate and disaggregate operators (e.g., by the use of OLAP tools). For instance, in a supermarket we may want to predict sales of ...
José Hernández-Orallo(Springer Verlag (Germany), 2015-05)
This paper presents a way to estimate the difficulty and discriminating power of
any task instance. We focus on a very general setting for tasks: interactive (possibly multiagent)
environments where an agent acts upon ...
Hernández Orallo, José; Dowe, David L.; España Cubillo, Sergio; Hernández-Lloreda, M. Victoria; Insa Cabrera, Javier(Springer Verlag (Germany), 2011)
One insightful view of the notion of intelligence is the ability
to perform well in a diverse set of tasks, problems or environments. One of
the key issues is therefore the choice of this set, which can be formalised
as ...
Bella Sanjuán, Antonio; Ferri Ramírez, César; José Hernández-Orallo; Ramírez Quintana, María José(Springer Verlag (Germany), 2012-06)
A general approach to classifier combination considers each model as a probabilistic classifier which outputs a class membership posterior probability. In this general scenario, it is not only the quality and diversity of ...
[EN] Machine teaching under strong simplicity priors can teach
any concept in universal languages. Remarkably, recent experiments suggest that the teaching sets are shorter than the concept description itself.
This raises ...
Hernández Orallo, José(Association for Computing Machinery (ACM), 2014-10)
Common-day applications of predictive models usually involve the full use of the available contextual information.
When the operating context changes, one may fine-tune the by-default (incontextual) prediction or
may ...
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 ...