Presently, inductive learning is still performed in a frustrating batch process. The user has little interaction with the system and no control over the final accuracy and traini...
Wei Fan, Haixun Wang, Philip S. Yu, Shaw-hwa Lo, S...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
Abstract. Adaptation of devices and applications based on contextual information has a great potential to enhance usability and mitigate the increasing complexity of mobile devices...
Keshu Zhang, Haifeng Li, Kari Torkkola, Mike Gardn...
Abstract. We present first experiments using Support Vector Regression as function approximator for an on-line, sarsa-like reinforcement learner. To overcome the batch nature of S...
The dramatic growth in the number and size of on-line information sources has fueled increasing research interest in the incremental subspace learning problem. In this paper, we pr...