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5 papers · 2 filters
Active Imitation Learning via Reduction to I.I.D. Active Learning
Kshitij Judah, Alan Fern, Thomas G. Dietterich
In standard passive imitation learning, the goal is to learn a target policy by passively observing full execution trajectories of it. Unfortunately, generating such trajectories c…
Learning from Sparse Data by Exploiting Monotonicity Constraints
Eric E. Altendorf, Angelo C. Restificar, Thomas G. Dietterich
When training data is sparse, more domain knowledge must be incorporated into the learning algorithm in order to reduce the effective size of the hypothesis space. This paper build…
Output Space Search for Structured Prediction
Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli
We consider a framework for structured prediction based on search in the space of complete structured outputs. Given a structured input, an output is produced by running a time-bou…
Batch Active Learning via Coordinated Matching
Javad Azimi, Alan Fern, Xiaoli Zhang-Fern +2
Most prior work on active learning of classifiers has focused on sequentially selecting one unlabeled example at a time to be labeled in order to reduce the overall labeling effort…
A Lipschitz Exploration-Exploitation Scheme for Bayesian Optimization
Ali Jalali, Javad Azimi, Xiaoli Fern +1
The problem of optimizing unknown costly-to-evaluate functions has been studied for a long time in the context of Bayesian Optimization. Algorithms in this field aim to find the op…