Discrete optimization
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Selective Sampling Using the Query by Committee Algorithm
Machine Learning
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Query by committee, linear separation and random walks
Theoretical Computer Science
Toward Optimal Active Learning through Sampling Estimation of Error Reduction
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Less is More: Active Learning with Support Vector Machines
ICML '00 Proceedings of the Seventeenth International Conference on 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
Employing EM and Pool-Based Active Learning for Text Classification
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Active Learning to Recognize Multiple Types of Plankton
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Active feedback in ad hoc information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
IEEE Transactions on Image Processing
Proceedings of the 25th international conference on Machine learning
A bayesian logistic regression model for active relevance feedback
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
trNon-greedy active learning for text categorization using convex ansductive experimental design
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
On profiling blogs with representative entries
Proceedings of the second workshop on Analytics for noisy unstructured text data
Cascade RSVM in Peer-to-Peer Networks
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Improving supervised learning performance by using fuzzy clustering method to select training data
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Fuzzy theory and technology with applications
Semisupervised SVM batch mode active learning with applications to image retrieval
ACM Transactions on Information Systems (TOIS)
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
Near-optimal observation selection using submodular functions
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Unsupervised active learning based on hierarchical graph-theoretic clustering
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multi-modal multi-label semantic indexing of images based on hybrid ensemble learning
PCM'07 Proceedings of the multimedia 8th Pacific Rim conference on Advances in multimedia information processing
Multiple-view multiple-learner active learning
Pattern Recognition
SED: supervised experimental design and its application to text classification
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Active learning with extremely sparse labeled examples
Neurocomputing
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
Active learning in multimedia annotation and retrieval: A survey
ACM Transactions on Intelligent Systems and Technology (TIST)
Active learning from stream data using optimal weight classifier ensemble
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Ask me better questions: active learning queries based on rule induction
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Discriminative experimental design
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Optimal batch selection for active learning in multi-label classification
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Batch Mode Active Learning for Networked Data
ACM Transactions on Intelligent Systems and Technology (TIST)
Batch mode active sampling based on marginal probability distribution matching
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Generating balanced classifier-independent training samples from unlabeled data
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Activized learning: transforming passive to active with improved label complexity
The Journal of Machine Learning Research
Robust active learning for linear regression via density power divergence
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Active hashing and its application to image and text retrieval
Data Mining and Knowledge Discovery
Active learning for interactive segmentation with expected confidence change
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Querying discriminative and representative samples for batch mode active learning
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Cost-sensitive online active learning with application to malicious URL detection
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Batch Mode Active Sampling Based on Marginal Probability Distribution Matching
ACM Transactions on Knowledge Discovery from Data (TKDD) - Special Issue on ACM SIGKDD 2012
Active learning for noisy oracle via density power divergence
Neural Networks
Active learning from relative queries
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Self-help: Seeking out perplexing images for ever improving topological mapping
International Journal of Robotics Research
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The goal of active learning is to select the most informative examples for manual labeling. Most of the previous studies in active learning have focused on selecting a single unlabeled example in each iteration. This could be inefficient since the classification model has to be retrained for every labeled example. In this paper, we present a framework for "batch mode active learning" that applies the Fisher information matrix to select a number of informative examples simultaneously. The key computational challenge is how to efficiently identify the subset of unlabeled examples that can result in the largest reduction in the Fisher information. To resolve this challenge, we propose an efficient greedy algorithm that is based on the property of submodular functions. Our empirical studies with five UCI datasets and one real-world medical image classification show that the proposed batch mode active learning algorithm is more effective than the state-of-the-art algorithms for active learning.