Instance-Based Learning Algorithms
Machine Learning
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Information-based objective functions for active data selection
Neural Computation
Improving Generalization with Active Learning
Machine Learning - Special issue on structured connectionist systems
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Intelligent Selection of Instances for Prediction Functions in LazyLearning Algorithms
Artificial Intelligence Review - Special issue on lazy learning
Selective Sampling Using the Query by Committee Algorithm
Machine Learning
Active Learning with Local Models
Neural Processing Letters
Bayesian Classification With Gaussian Processes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Selective sampling for nearest neighbor classifiers
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Reduction Techniques for Instance-BasedLearning Algorithms
Machine Learning
Machine Learning
Machine Learning
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Active Learning of the Generalized High-Low Game
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
Active Learning with Statistical Models
Active Learning with Statistical Models
Journal of Artificial Intelligence Research
Lookahead and pathology in decision tree induction
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
The farthest point strategy for progressive image sampling
IEEE Transactions on Image Processing
Online Choice of Active Learning Algorithms
The Journal of Machine Learning Research
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Anytime Learning of Decision Trees
The Journal of Machine Learning Research
Active learning for real-time motion controllers
ACM SIGGRAPH 2007 papers
A nearest-neighbor approach to relevance feedback in content based image retrieval
Proceedings of the 6th ACM international conference on Image and video retrieval
Expert Systems with Applications: An International Journal
Using active learning to annotate microscope images of parasite eggs
Artificial Intelligence Review
Active learning with direct query construction
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Selective generation of training examples in active meta-learning
International Journal of Hybrid Intelligent Systems - HIS 2007
Feature Selection Using Mutual Information: An Experimental Study
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Feature selection with dynamic mutual information
Pattern Recognition
Active learning for directed exploration of complex systems
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Active learning with near misses
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Active learning with multiple views
Journal of Artificial Intelligence Research
Active Generation of Training Examples in Meta-Regression
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
An improved sample selection algorithm in fuzzy decision tree induction
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Active learning to support the generation of meta-examples
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Active learning for regression based on query by committee
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Asking generalized queries to ambiguous oracle
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Complexity bounds for batch active learning in classification
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Combining meta-learning and active selection of datasetoids for algorithm selection
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
Uncertainty sampling-based active selection of datasetoids for meta-learning
ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
Active learning for sparse least squares support vector machines
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part II
Budgeted learning of nailve-bayes classifiers
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Noisy data elimination using mutual k-nearest neighbor for classification mining
Journal of Systems and Software
Combining Uncertainty Sampling methods for supporting the generation of meta-examples
Information Sciences: an International Journal
EGAL: exploration guided active learning for TCBR
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
The Journal of Machine Learning Research
Inconsistency-based active learning for support vector machines
Pattern Recognition
Activized learning: transforming passive to active with improved label complexity
The Journal of Machine Learning Research
Enhancing image retrieval by an exploration-exploitation approach
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
k nearest neighbor using ensemble clustering
DaWaK'12 Proceedings of the 14th international conference on Data Warehousing and Knowledge Discovery
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
CrowdMiner: mining association rules from the crowd
Proceedings of the VLDB Endowment
Pattern classification and clustering: A review of partially supervised learning approaches
Pattern Recognition Letters
An ensemble-clustering-based distance metric and its applications
International Journal of Business Intelligence and Data Mining
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Most existing inductive learning algorithms work under the assumption that their training examples are already tagged. There are domains, however, where the tagging procedure requires significant computation resources or manual labor. In such cases, it may be beneficial for the learner to be active, intelligently selecting the examples for labeling with the goal of reducing the labeling cost. In this paper we present LSS—a lookahead algorithm for selective sampling of examples for nearest neighbor classifiers. The algorithm is looking for the example with the highest utility, taking its effect on the resulting classifier into account. Computing the expected utility of an example requires estimating the probability of its possible labels. We propose to use the random field model for this estimation. The LSS algorithm was evaluated empirically on seven real and artificial data sets, and its performance was compared to other selective sampling algorithms. The experiments show that the proposed algorithm outperforms other methods in terms of average error rate and stability.