In the last years, a growing interest in the field of Machine Learning and of Statistical Learning Theory has pervaded both the academic and the industry areas. This is mainly due to the fact that the learning paradigm supplies a framework where no need for a-priori knowledge about the specifically targeted discipline is required. Besides, the World Wide Web has established as the most popular way to connect and communicate. A web-enabled server is proposed, to allow users launch various learning algorithms on their own data, with the purpose of deriving a nonlinear model. The system is built on a cluster of workstations running LINUX and is capable of adapt itself by optimally balancing the computational load at run-time. The users can send their data to the server through a WWW upload form, and the solution is sent back via e-mail at the end of the elaboration.
The ISAAC server: a proposal for smart algorithms delivering
ANGUITA, DAVIDE;
2003-01-01
Abstract
In the last years, a growing interest in the field of Machine Learning and of Statistical Learning Theory has pervaded both the academic and the industry areas. This is mainly due to the fact that the learning paradigm supplies a framework where no need for a-priori knowledge about the specifically targeted discipline is required. Besides, the World Wide Web has established as the most popular way to connect and communicate. A web-enabled server is proposed, to allow users launch various learning algorithms on their own data, with the purpose of deriving a nonlinear model. The system is built on a cluster of workstations running LINUX and is capable of adapt itself by optimally balancing the computational load at run-time. The users can send their data to the server through a WWW upload form, and the solution is sent back via e-mail at the end of the elaboration.
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