Abundant data is the key to successful machine learning. However, supervised learning requires annotated data that are often hard to obtain. In a classification task with limited resources, Active Learning (AL) promises to guide annotators to examples that bring the most value for a classifier. AL can be successfully combined with self-training, i.e., extending a training set with the unlabelled examples for which a classifier is the most certain. We report our experiences on using AL in a systematic manner to train an SVM classifier for Stack Overflow posts discussing performance of software components. We show that the training examples deemed as the most valuable to the classifier are also the most difficult for humans to annotate. Despi...
Crowdsourcing platforms offer a practical solution to the problem of afford-ably annotating large da...
Active learning promises to improve annotation efficiency by iteratively selecting the most importan...
We study the problem of combining active learning suggestions to identify informative training examp...
Abundant data is the key to successful machine learning. However, supervised learning requires annot...
ii With the proliferation of social media, gathering data has became cheaper and easier than before....
With the proliferation of social media, gathering data has became cheaper and easier than before. Ho...
In recent decades, the availability of a large amount of data has propelled the field of machine lea...
Despite the availability and ease of collecting a large amount of free, unlabeled data, the expensiv...
The key idea behind active learning is that a machine learning algorithm can achieve greater accurac...
In machine learning, active learning refers to algorithms that autonomously select the data points f...
Traditional supervised machine learning algorithms are expected to have access to a large corpus of ...
A common obstacle preventing the rapid deployment of supervised machine learning algorithms is the l...
Recent decades have witnessed great success of machine learning, especially for tasks where large an...
Active learning seeks to train the best classifier at the lowest annotation cost by intelligently pi...
Active learning is a supervised machine learning technique in which the learner is in control of the...
Crowdsourcing platforms offer a practical solution to the problem of afford-ably annotating large da...
Active learning promises to improve annotation efficiency by iteratively selecting the most importan...
We study the problem of combining active learning suggestions to identify informative training examp...
Abundant data is the key to successful machine learning. However, supervised learning requires annot...
ii With the proliferation of social media, gathering data has became cheaper and easier than before....
With the proliferation of social media, gathering data has became cheaper and easier than before. Ho...
In recent decades, the availability of a large amount of data has propelled the field of machine lea...
Despite the availability and ease of collecting a large amount of free, unlabeled data, the expensiv...
The key idea behind active learning is that a machine learning algorithm can achieve greater accurac...
In machine learning, active learning refers to algorithms that autonomously select the data points f...
Traditional supervised machine learning algorithms are expected to have access to a large corpus of ...
A common obstacle preventing the rapid deployment of supervised machine learning algorithms is the l...
Recent decades have witnessed great success of machine learning, especially for tasks where large an...
Active learning seeks to train the best classifier at the lowest annotation cost by intelligently pi...
Active learning is a supervised machine learning technique in which the learner is in control of the...
Crowdsourcing platforms offer a practical solution to the problem of afford-ably annotating large da...
Active learning promises to improve annotation efficiency by iteratively selecting the most importan...
We study the problem of combining active learning suggestions to identify informative training examp...