Add to ORKGAbstract — An active learner is given an instance space, a label space and a hypothesis class, where one of the hypotheses in the class assigns ground truth labels to instances. Additionally, the learner has access to a labeling oracle, which it can interactively query for the label of any example in the instance space. The goal of the learner is to find a good estimate of the hypothesis in the hypothesis class that generates the ground truth labels while making as few interactive queries to the oracle as possible. This work considers a more general setting where the labeling oracle can abstain from providing a label in addition to returning noisy labels. We provide a model for this setting where the abstention rate and the noise rate incre...
AbstractThe present paper deals with several variants of inductive inference from noisy data. The no...
We consider the problem of active sequential hypothesis testing where a Bayesian\u3cbr/\u3edecision ...
We consider the problem of active sequential hypothesis testing where a Bayesiandecision maker must ...
We study active learning where the labeler can not only return incorrect labels but also abstain fro...
We study active learning where the labeler can not only return incorrect labels but also abstain fro...
We study pool-based active learning with abstention feedbacks, where a labeler can abstain from labe...
Recent decades have witnessed great success of machine learning, especially for tasks where large an...
Recent decades have witnessed great success of machine learning, especially for tasks where large an...
This dissertation develops and analyzes active learning algorithms for binary classification problem...
In active learning, the user sequentially chooses values for feature X and an oracle returns the cor...
<p>In this paper we propose and study a generalization of the standard active-learning model where a...
In this paper we propose and study a generalization of the standard active-learning model where a mo...
AbstractWe state and analyze the first active learning algorithm that finds an ϵ-optimal hypothesis ...
The goal of active learning is to achieve the same accuracy achievable by passive learning, while us...
The original and most widely studied PAC model for learning assumes a passive learner in the sense t...
AbstractThe present paper deals with several variants of inductive inference from noisy data. The no...
We consider the problem of active sequential hypothesis testing where a Bayesian\u3cbr/\u3edecision ...
We consider the problem of active sequential hypothesis testing where a Bayesiandecision maker must ...
We study active learning where the labeler can not only return incorrect labels but also abstain fro...
We study active learning where the labeler can not only return incorrect labels but also abstain fro...
We study pool-based active learning with abstention feedbacks, where a labeler can abstain from labe...
Recent decades have witnessed great success of machine learning, especially for tasks where large an...
Recent decades have witnessed great success of machine learning, especially for tasks where large an...
This dissertation develops and analyzes active learning algorithms for binary classification problem...
In active learning, the user sequentially chooses values for feature X and an oracle returns the cor...
<p>In this paper we propose and study a generalization of the standard active-learning model where a...
In this paper we propose and study a generalization of the standard active-learning model where a mo...
AbstractWe state and analyze the first active learning algorithm that finds an ϵ-optimal hypothesis ...
The goal of active learning is to achieve the same accuracy achievable by passive learning, while us...
The original and most widely studied PAC model for learning assumes a passive learner in the sense t...
AbstractThe present paper deals with several variants of inductive inference from noisy data. The no...
We consider the problem of active sequential hypothesis testing where a Bayesian\u3cbr/\u3edecision ...
We consider the problem of active sequential hypothesis testing where a Bayesiandecision maker must ...