
Topic
- Computing and Processing
- Components, Circuits, Devices and Systems
- Communication, Networking and Broadcast Technologies
- Power, Energy and Industry Applications
- Signal Processing and Analysis
- Robotics and Control Systems
- General Topics for Engineers
- Fields, Waves and Electromagnetics
- Engineered Materials, Dielectrics and Plasmas
- Bioengineering
- Transportation
- Photonics and Electrooptics
- Engineering Profession
- Aerospace
- Geoscience
- Nuclear Engineering
- Career Development
- Emerging Technologies
- Telecommunications
- English for Technical Professionals
F. J. Corbacho
Also published under:F. Corbacho
Affiliation
Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
Topic
Error Rate,Evolutionary Algorithms,Functional Link Network,Higher-order Networks,Learning Algorithms,Multilayer Perceptron,Polynomial Terms,Training Set,Validation Set,Adaptive System,Agent Dynamics,Amount Of Processing,Autonomous Agents,Backpropagation,Behavior Of Agents,Breast Cancer,Clustering Coefficient,Complex Architecture,Computational Point Of View,Construction Algorithm,Construction Cost,Decision Tree,Decision Tree Construction,Discretion,Dynamic Network,Dynamical,Efficient Algorithm,Eigenvectors,Extract Relevant Information,Fine Needle Aspiration,Fitness Function,Global Search,Hidden Layer,High Reliability,Hilbert Space,Independent Component Analysis,Individuals In Generation,Information Gain,Information Processing,Information Theory,Input Attributes,Input Layer,Input Noise,Learning Rule,Linear Network,Local Interactions,Local Minima,Local Properties,Maximum Mutual Information,Multi-agent Networks,
Biography
Fernando J. Corbacho received the B.Sc. degree (magna cum laude) from the University of Minnesota, MN, in 1990, and the M.Sc. and Ph.D. degrees in computer science from the University of Southern California, Los Angeles, CA, in 1993 and 1997, respectively.
He is currently an Ad Honorem Professor in the Computer Science Departmen, Universidad Autónoma de Madrid, Spain and Co-founder and Chief Technology Officer of Cognodata, Madrid, Spain. Cognodata is a firm specialized in the use of data mining and artificial intelligence technics to solve business problems specially in the area of marketing intelligence. He is engaged in the development of a theory of organization for adaptive autonomous agents. His main reserach interests include machine learning, schema-based learning, and the emergence of intelligence. He is a member of several computer and neuroscience associations.
He is currently an Ad Honorem Professor in the Computer Science Departmen, Universidad Autónoma de Madrid, Spain and Co-founder and Chief Technology Officer of Cognodata, Madrid, Spain. Cognodata is a firm specialized in the use of data mining and artificial intelligence technics to solve business problems specially in the area of marketing intelligence. He is engaged in the development of a theory of organization for adaptive autonomous agents. His main reserach interests include machine learning, schema-based learning, and the emergence of intelligence. He is a member of several computer and neuroscience associations.