Add to ORKGIn this paper, an on-line interactive method is proposed for learning a linear classifier. This problem is studied within the Active Learning (AL) framework where the learning algorithm sequentially chooses unlabelled training samples and requests their class labels from an oracle in order to learn the classifier with the least queries to the oracle possible. Additionally' a constraint is introduced into this interactive learning process which limits the percentage of the samples from one “unwanted” class under a certain threshold. An optimal AL solution is derived and implemented with a sophisticated, accurate and fast Bayesian Learning method, the Expectation Propagation (EP) and its performance is demonstrated through numerical simulatio...
In machine learning, active class selection (ACS) algorithms aim to actively select a class and ask ...
We approach the problem of active learning from a Bayesian perspective, working with a probability d...
Over the last decade there has been growing interest in pool-based active learning techniques, where...
peer reviewedIn this paper, an on-line interactive method is proposed for learning a linear classifi...
There has been growing recent interest in the field of active learning for binary classification. Th...
Abstract—We develop an active learning algorithm for kernel-based linear regression and classificati...
With the advent of the Internet and growth of storage capabilities, large collections of unlabelled ...
Bayesian networks are graphical representations of probability distributions. In virtually all of th...
Copyright © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obta...
With active learning the learner participates in the process of selecting instances so as to speed-u...
We study the problem of active learning for multilabel clas-sification. We focus on the real-world s...
In recent decades, the availability of a large amount of data has propelled the field of machine lea...
International audienceIn this paper, we propose to reformulate the active learning problem occurring...
Traditionally, Bayesian inductive learning involves finding the most probable model from the entire ...
In many settings in practice it is expensive to obtain labeled data while unlabeled data is abundant...
In machine learning, active class selection (ACS) algorithms aim to actively select a class and ask ...
We approach the problem of active learning from a Bayesian perspective, working with a probability d...
Over the last decade there has been growing interest in pool-based active learning techniques, where...
peer reviewedIn this paper, an on-line interactive method is proposed for learning a linear classifi...
There has been growing recent interest in the field of active learning for binary classification. Th...
Abstract—We develop an active learning algorithm for kernel-based linear regression and classificati...
With the advent of the Internet and growth of storage capabilities, large collections of unlabelled ...
Bayesian networks are graphical representations of probability distributions. In virtually all of th...
Copyright © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obta...
With active learning the learner participates in the process of selecting instances so as to speed-u...
We study the problem of active learning for multilabel clas-sification. We focus on the real-world s...
In recent decades, the availability of a large amount of data has propelled the field of machine lea...
International audienceIn this paper, we propose to reformulate the active learning problem occurring...
Traditionally, Bayesian inductive learning involves finding the most probable model from the entire ...
In many settings in practice it is expensive to obtain labeled data while unlabeled data is abundant...
In machine learning, active class selection (ACS) algorithms aim to actively select a class and ask ...
We approach the problem of active learning from a Bayesian perspective, working with a probability d...
Over the last decade there has been growing interest in pool-based active learning techniques, where...