COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
A sequential algorithm for training text classifiers
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Selective Sampling Using the Query by Committee Algorithm
Machine Learning
Further results on the margin distribution
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Introduction: personalized views of personalization
Communications of the ACM
Solving convex programs by random walks
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Machine Learning
Machine Learning
Query Learning with Large Margin Classifiers
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Support Vector Machine Active Learning with Application sto Text Classification
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Machine Learning for Adaptive User Interfaces
KI '97 Proceedings of the 21st Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
Estimating the Support of a High-Dimensional Distribution
Neural Computation
Journal of Artificial Intelligence Research
SVM selective sampling for ranking with application to data retrieval
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Preference learning with Gaussian processes
ICML '05 Proceedings of the 22nd international conference on Machine learning
Entropy-Driven online active learning for interactive calendar management
Proceedings of the 12th international conference on Intelligent user interfaces
Active exploration for learning rankings from clickthrough data
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Optimizing estimated loss reduction for active sampling in rank learning
Proceedings of the 25th international conference on Machine learning
Active Sampling for Rank Learning via Optimizing the Area under the ROC Curve
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
RankSVR: can preference data help regression?
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Fast active exploration for link-based preference learning using Gaussian processes
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Selective sampling techniques for feedback-based data retrieval
Data Mining and Knowledge Discovery
Detecting and ordering salient regions
Data Mining and Knowledge Discovery
A selective sampling strategy for label ranking
ECML'06 Proceedings of the 17th European conference on Machine Learning
ECML'06 Proceedings of the 17th European conference on Machine Learning
Efficiently learning the preferences of people
Machine Learning
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The effort necessary to construct labeled sets of examples in a supervised learning scenario is often disregarded, though in many applications, it is a time-consuming and expensive procedure. While this already constitutes a major issue in classification learning, it becomes an even more serious problem when dealing with the more complex target domain of total orders over a set of alternatives. Considering both the pairwise decomposition and the constraint classification technique to represent label ranking functions, we introduce a novel generalization of pool-based active learning to address this problem.