Developing automated agents that intelligently perform complex real world tasks is time consuming and expensive. The most expensive part of developing these intelligent task perfo...
Most theoretical models of inductive inference make the idealized assumption that the data available to a learner is from a single and accurate source. The subject of inaccuracies ...
POIROT is an integration framework for combining machine learning mechanisms to learn hierarchical models of web services procedures from a single or very small set of demonstrati...
Mark H. Burstein, Robert Laddaga, David McDonald, ...
— In recent years, learning models from data has become an increasingly interesting tool for robotics, as it allows straightforward and accurate model approximation. However, in ...
The problem of multimodal data mining in a multimedia database can be addressed as a structured prediction problem where we learn the mapping from an input to the structured and i...
Zhen Guo, Zhongfei Zhang, Eric P. Xing, Christos F...