The goal of active learning is to determine the locations of training input points so that the generalization error is minimized.

Abstract. The goal of active learning is to determine the locations of training input points so that the general- ization error is minimized.

The goal of active learning is to determine the locations of training input points so that the generalization error is minimized. We discuss the problem of ...

The goal of active learning is to determine the locations of training input points so that the generalization error is minimized. We discuss the problem of ...

Abstract. The goal of pool-based active learning is to choose the best input points to gather output values from a 'pool' of input samples.

This chapter contains sections titled: Conditional Expectation Analysis of Generalization Error, Linear Regression under Covariate Shift, Model Selection, ...

Jan 30, 2009 · The goal of pool-based active learning is to choose the best input points to gather output values from a 'pool' of input samples.

Active learning in approximately linear regression based on conditional expectation of generalization error. Journal of Machine Learning Research, 7:141–166,.

In this paper, we suggest a new algorithm for active learning (ALA) which converges to the optimal parameter as the number of the sample goes to infinity even ...

▫Thus generalization error estimation in active learning would be harder than ... based on Conditional Expectation of generalization error. Page 30. 30.