Information-based objective functions for active data selection
Neural Computation
Sparse Approximate Solutions to Linear Systems
SIAM Journal on Computing
Selective Sampling Using the Query by Committee Algorithm
Machine Learning
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
Robustness of regularized linear classification methods in text categorization
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Active learning: theory and applications
Active learning: theory and applications
Use of the zero norm with linear models and kernel methods
The Journal of Machine Learning Research
Convergence of alternating optimization
Neural, Parallel & Scientific Computations
Convex Optimization
Near-optimal sensor placements in Gaussian processes
ICML '05 Proceedings of the 22nd international conference on Machine learning
Active learning with statistical models
Journal of Artificial Intelligence Research
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Laplacian optimal design for image retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Query rewriting using active learning for sponsored search
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Repairing self-confident active-transductive learners using systematic exploration
Pattern Recognition Letters
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
The Journal of Machine Learning Research
Active relevance feedback for difficult queries
Proceedings of the 17th ACM conference on Information and knowledge management
Advertising keyword generation using active learning
Proceedings of the 18th international conference on World wide web
Uncertainty sampling and transductive experimental design for active dual supervision
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Convex experimental design using manifold structure for image retrieval
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Curiosity driven incremental LDA agent active learning
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Feature Selection for Gene Expression Using Model-Based Entropy
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
LIBGS: A MATLAB software package for gene selection
International Journal of Data Mining and Bioinformatics
Laplacian regularized D-optimal design for active learning and its application to image retrieval
IEEE Transactions on Image Processing
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
Locally regressive G-optimal design for image retrieval
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
SALSAS: Sub-linear active learning strategy with approximate k-NN search
Pattern Recognition
Active learning with adaptive regularization
Pattern Recognition
Efficient manifold ranking for image retrieval
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Dual active feature and sample selection for graph classification
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Semi-supervised dimensionality reduction via harmonic functions
MDAI'11 Proceedings of the 8th international conference on Modeling decisions for artificial intelligence
Discriminative experimental design
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
DClusterE: A Framework for Evaluating and Understanding Document Clustering Using Visualization
ACM Transactions on Intelligent Systems and Technology (TIST)
Active learning with semi-automatic annotation for extractive speech summarization
ACM Transactions on Speech and Language Processing (TSLP)
The Journal of Machine Learning Research
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Batch mode active sampling based on marginal probability distribution matching
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Comparative document summarization via discriminative sentence selection
ACM Transactions on Knowledge Discovery from Data (TKDD)
Efficiently learning the preferences of people
Machine Learning
Active hashing and its application to image and text retrieval
Data Mining and Knowledge Discovery
Comparative Document Summarization via Discriminative Sentence Selection
ACM Transactions on Knowledge Discovery from Data (TKDD)
Learning a subspace for clustering via pattern shrinking
Information Processing and Management: an International Journal
Querying discriminative and representative samples for batch mode active learning
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
On learning-based methods for design-space exploration with high-level synthesis
Proceedings of the 50th Annual Design Automation Conference
Batch Mode Active Sampling Based on Marginal Probability Distribution Matching
ACM Transactions on Knowledge Discovery from Data (TKDD) - Special Issue on ACM SIGKDD 2012
TopicDSDR: combining topic decomposition and data reconstruction for summarization
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Active learning via neighborhood reconstruction
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Early active learning via robust representation and structured sparsity
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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This paper considers the problem of selecting the most informative experiments x to get measurements y for learning a regression model y = f(x). We propose a novel and simple concept for active learning, transductive experimental design, that explores available unmeasured experiments (i.e., unlabeled data) and has a better scalability in comparison with classic experimental design methods. Our in-depth analysis shows that the new method tends to favor experiments that are on the one side hard-to-predict and on the other side representative for the rest of the experiments. Efficient optimization of the new design problem is achieved through alternating optimization and sequential greedy search. Extensive experimental results on synthetic problems and three real-world tasks, including questionnaire design for preference learning, active learning for text categorization, and spatial sensor placement, highlight the advantages of the proposed approaches.