Add to ORKGWe investigate the problem of active learning on a given tree whose nodes are assigned binary labels in an adversarial way. Inspired by recent results by Guillory and Bilmes, we characterize(up to constant factors) the optimal placement of queries so to minimize the mistakes made on the non-queried nodes. Our query selection algorithm is extremely ef\ufb01cient, and the optimal number of mistakes on the non-queried nodes is achieved by a simple and ef\ufb01cient mincut classi\ufb01er. Through a simple modi\ufb01cation of the query selection algorithm we also show optimality (up to constant factors) with respect to the trade-off between number of queries and number of mistakes on nonqueried nodes. By using spanning trees, our algorithms can ...
Traditional active learning methods require the labeler to provide a class label for each queried in...
International audienceWe investigate active learning by pairwise similarity over the leaves of trees...
The key idea behind active learning is that a machine learning algorithm can achieve greater accurac...
Active learning algorithms for graph node classification select a subset L of nodes in a given graph...
This paper investigates the problem of active learning for binary label prediction on a graph. We in...
Abstract—Active learning on graphs has received increas-ing interest in the past years. In this pape...
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...
We present very efficient active learning algorithms for link classification in signed networks. Our...
Traditional active learning methods request experts to provide ground truths to the queried instance...
We study active learning where the labeler can not only return incorrect labels but also abstain fro...
We present very efficient active learning algorithms for link classification in signed networks. Our...
In many classification problems, including numerous exam-ples on modern large-scale graph datasets, ...
We are living in the Internet Age, in which information entities and objects are interconnected, the...
The field of Machine Learning is concerned with the development of algorithms, models and techniques...
Traditional active learning methods require the labeler to provide a class label for each queried in...
International audienceWe investigate active learning by pairwise similarity over the leaves of trees...
The key idea behind active learning is that a machine learning algorithm can achieve greater accurac...
Active learning algorithms for graph node classification select a subset L of nodes in a given graph...
This paper investigates the problem of active learning for binary label prediction on a graph. We in...
Abstract—Active learning on graphs has received increas-ing interest in the past years. In this pape...
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...
We present very efficient active learning algorithms for link classification in signed networks. Our...
Traditional active learning methods request experts to provide ground truths to the queried instance...
We study active learning where the labeler can not only return incorrect labels but also abstain fro...
We present very efficient active learning algorithms for link classification in signed networks. Our...
In many classification problems, including numerous exam-ples on modern large-scale graph datasets, ...
We are living in the Internet Age, in which information entities and objects are interconnected, the...
The field of Machine Learning is concerned with the development of algorithms, models and techniques...
Traditional active learning methods require the labeler to provide a class label for each queried in...
International audienceWe investigate active learning by pairwise similarity over the leaves of trees...
The key idea behind active learning is that a machine learning algorithm can achieve greater accurac...
