Inicio > > Ciencias de la computación > Inteligencia artificial > From Statistics to Neural Networks
From Statistics to Neural Networks

From Statistics to Neural Networks

 

133,32 €
IVA incluido
Disponible
Editorial:
Springer Nature B.V.
Año de edición:
2011
Materia
Inteligencia artificial
ISBN:
9783642791215
133,32 €
IVA incluido
Disponible

Selecciona una librería:

  • Librería Samer Atenea
  • Librería Aciertas (Toledo)
  • Kálamo Books
  • Librería Perelló (Valencia)
  • Librería Elías (Asturias)
  • Donde los libros
  • Librería Kolima (Madrid)
  • Librería Proteo (Málaga)

The NATO Advanced Study Institute From Statistics to Neural Networks, Theory and Pattern Recognition Applications took place in Les Arcs, Bourg Saint Maurice, France, from June 21 through July 2, 1993. The meeting brought to­ gether over 100 participants (including 19 invited lecturers) from 20 countries. The invited lecturers whose contributions appear in this volume are: L. Almeida (INESC, Portugal), G. Carpenter (Boston, USA), V. Cherkassky (Minnesota, USA), F. Fogelman Soulie (LRI, France), W. Freeman (Berkeley, USA), J. Friedman (Stanford, USA), F. Girosi (MIT, USA and IRST, Italy), S. Grossberg (Boston, USA), T. Hastie (AT&T, USA), J. Kittler (Surrey, UK), R. Lippmann (MIT Lincoln Lab, USA), J. Moody (OGI, USA), G. Palm (U1m, Germany), B. Ripley (Oxford, UK), R. Tibshirani (Toronto, Canada), H. Wechsler (GMU, USA), C. Wellekens (Eurecom, France) and H. White (San Diego, USA). The ASI consisted of lectures overviewing major aspects of statistical and neural network learning, their links to biological learning and non-linear dynamics (chaos), and real-life examples of pattern recognition applications. As a result of lively interactions between the participants, the following topics emerged as major themes of the meeting: (1) Unified framework for the study of Predictive Learning in Statistics and Artificial Neural Networks (ANNs); (2) Differences and similarities between statistical and ANN methods for non­ parametric estimation from examples (learning); (3) Fundamental connections between artificial learning systems and biological learning systems.

Artículos relacionados

  • Artificial Cognition Systems
    ...
  • Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition
    Vijay Kumar Mago
    The need for intelligent machines in areas such as medical diagnostics, biometric security systems, and image processing motivates researchers to develop and explore new techniques, algorithms, and applications in this evolving field. Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies provides a common platform for researc...
  • Emerging Applications of Natural Language Processing
    Over the last few years, the area of Natural Language Processing has drastically grown in recognition, not only within the research and development community, but also with industry professionals. As NLP continues to be discussed and researched, certain areas continue to grow and mature. As a result, the need for advanced research and information is in high demand. Emerging App...
  • Androids, Cyborgs, and Robots in Contemporary Culture and Society
    Steven John Thompson
    Mankind’s dependence on artificial intelligence and robotics is increasing rapidly as technology becomes more advanced. Finding a way to seamlessly intertwine these two worlds will help boost productivity in society and aid in a variety of ways in modern civilization. Androids, Cyborgs, and Robots in Contemporary Culture and Society is an essential scholarly resource that delve...
  • Deep Learning Innovations and Their Convergence With Big Data
    The expansion of digital data has transformed various sectors of business such as healthcare, industrial manufacturing, and transportation. A new way of solving business problems has emerged through the use of machine learning techniques in conjunction with big data analytics. Deep Learning Innovations and Their Convergence With Big Data is a pivotal reference for the latest sc...
  • Computational Psychoanalysis and Formal Bi-Logic Frameworks
    Giuseppe Iurato
    Computational psychoanalysis is a new field stemming from Freudian psychoanalysis. The new area aims to understand the primary formal structures and running mechanisms of the unconscious while implementing them into computer sciences. Computational Psychoanalysis and Formal Bi-Logic Frameworks provides emerging information on this new field which uses psychoanalysis and the unc...