Informes recientes muestran la creciente adopción en el sector financiero de técnicas de aprendizaje automático o machine learning (ML) en la gestión del riesgo de crédito. En este entorno, los supervisores se encuentran ante el reto de permitir que se maximicen las oportunidades derivadas...

Artículo de revista ; The use of artificial intelligence tools has escalated recently in all sectors of the economy owing, among other factors, to the growing volume of digital data and higher computational capacity. Major benefits may be reaped from applying these tools to the provision of...

Uno de los principales retos en el uso de modelos de aprendizaje automático, o machine learning en inglés (ML), en finanzas es cómo explicar sus resultados. Recientemente han aparecido técnicas de interpretabilidad con este objetivo, pero existe discusión sobre su fiabilidad. En este...

Recientes avances tecnológicos, como el almacenamiento masivo de datos y la computación en la nube, están dando lugar a un mayor uso de la inteligencia artificial en la economía y las finanzas, y modificando aspectos fundamentales tanto para entidades como para supervisores. En este...

The decision tree is a well-known methodology for classification and regression. In this dissertation, we focus on the minimization of the misclassification rate for decision tree classifiers. We derive the necessary equations that provide the optimal tree prediction, the estimated risk of the...

The study of complex systems should be based on a systems-theoretic framework which requires both self-organizing and symbolic dimensions. An inclusive framework based on the notion of semiotics is advanced to build models capable of representing, as well as evolving in their environments, with...

We identify a general framework for weak planning called bootstrap planning, which is defined as global planning using only a local planner along with some memory for learning intermediate subgoals. We present a family of algorithms for bootstrap planning, and provide some initial theory on...

There is a recognised need for the continued improvement of both the techniques and technology for spatial decision support in infrastructure site selection. Many authors have noted that current methodologies are inadequate for real-world site selection decisions carried out by heterogeneous...

When large numbers of alerts are reported by intrusion detection (ID) systems in very fine granularity, it prevents system administrators from handling the alerts effectively. This in turn degrades the usability of an intrusion detection system. Aside from detection, timely responses of...

Machine learning has become one of the most active and exciting areas of computer science research, in large part because of its wide-spread applicability to problems as diverse as natural language processing, speech recognition, spam detection, search, computer vision, gene discovery, medical...