Exploring Representativeness and Informativeness for Active Learning
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Wei Liu | Bo Du | Liangpei Zhang | Dacheng Tao | Jialie Shen | Zengmao Wang | Lefei Zhang | W. Liu | D. Tao | Liang-pei Zhang | Bo Du | Lefei Zhang | Jialie Shen | Zengmao Wang | Liangpei Zhang
[1] P. Hall. Central limit theorem for integrated square error of multivariate nonparametric density estimators , 1984 .
[2] Colin McDiarmid,et al. Surveys in Combinatorics, 1989: On the method of bounded differences , 1989 .
[3] N. H. Anderson,et al. Two-sample test statistics for measuring discrepancies between two multivariate probability density functions using kernel-based density estimates , 1994 .
[4] Daphne Koller,et al. Support Vector Machine Active Learning with Applications to Text Classification , 2000, J. Mach. Learn. Res..
[5] Raymond J. Mooney,et al. Diverse ensembles for active learning , 2004, ICML.
[6] Burr Settles,et al. Active Learning Literature Survey , 2009 .
[7] Wei Hu,et al. Unsupervised Active Learning Based on Hierarchical Graph-Theoretic Clustering , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[8] Rajeev Alur,et al. Active Learning of Plans for Safety and Reachability Goals With Partial Observability , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[9] Xiaodong Lin,et al. Active Learning From Stream Data Using Optimal Weight Classifier Ensemble , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[10] Friedhelm Schwenker,et al. Combining Committee-Based Semi-Supervised Learning and Active Learning , 2010, Journal of Computer Science and Technology.
[11] Xiaofei He,et al. Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval , 2010, IEEE Transactions on Image Processing.
[12] Meng Wang,et al. Active learning in multimedia annotation and retrieval: A survey , 2011, TIST.
[13] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[14] Isabelle Guyon,et al. Results of the Active Learning Challenge , 2011, Active Learning and Experimental Design @ AISTATS.
[15] Chun Chen,et al. Active Learning Based on Locally Linear Reconstruction , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[16] Foster J. Provost,et al. Online active inference and learning , 2011, KDD.
[17] Ke Chen,et al. Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[18] Bernhard Schölkopf,et al. A Kernel Two-Sample Test , 2012, J. Mach. Learn. Res..
[19] Jingbo Zhu,et al. Uncertainty-based active learning with instability estimation for text classification , 2012, TSLP.
[20] Mijung Park,et al. Bayesian active learning with localized priors for fast receptive field characterization , 2012, NIPS.
[21] Xiao Li,et al. Active Learning for Hierarchical Text Classification , 2012, PAKDD.
[22] Nikolaos Papanikolopoulos,et al. Scalable Active Learning for Multiclass Image Classification , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[23] Sethuraman Panchanathan,et al. Joint Transfer and Batch-mode Active Learning , 2013, ICML.
[24] Javier Pérez-Rodríguez,et al. OligoIS: Scalable Instance Selection for Class-Imbalanced Data Sets , 2013, IEEE Transactions on Cybernetics.
[25] Andreas Krause,et al. Active Learning for Multi-Objective Optimization , 2013, ICML.
[26] Pingkun Yan,et al. Image Super-Resolution Via Double Sparsity Regularized Manifold Learning , 2013, IEEE Transactions on Circuits and Systems for Video Technology.
[27] Shai Shalev-Shwartz,et al. Efficient active learning of halfspaces: an aggressive approach , 2012, J. Mach. Learn. Res..
[28] Xuelong Li,et al. Person Re-Identification by Regularized Smoothing KISS Metric Learning , 2013, IEEE Transactions on Circuits and Systems for Video Technology.
[29] Nan Ye,et al. Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion , 2013, NIPS.
[30] Xuelong Li,et al. Manifold Regularized Sparse NMF for Hyperspectral Unmixing , 2013, IEEE Transactions on Geoscience and Remote Sensing.
[31] Ke Tang,et al. Combining Semi-Supervised and active learning for hyperspectral image classification , 2013, 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).
[32] Sethuraman Panchanathan,et al. Batch mode active sampling based on marginal probability distribution matching , 2012, TKDD.
[33] Jieping Ye,et al. Querying discriminative and representative samples for batch mode active learning , 2013, KDD.
[34] Allen Y. Yang,et al. A Convex Optimization Framework for Active Learning , 2013, 2013 IEEE International Conference on Computer Vision.
[35] Jie Yin,et al. Knowledge Transfer for Multi-labeler Active Learning , 2013, ECML/PKDD.
[36] Friedhelm Schwenker,et al. Semi-supervised Learning , 2013, Handbook on Neural Information Processing.
[37] Yulong Wang,et al. Sparse Coding From a Bayesian Perspective , 2013, IEEE Transactions on Neural Networks and Learning Systems.
[38] Yulong Wang,et al. Graph-Regularized Low-Rank Representation for Destriping of Hyperspectral Images , 2013, IEEE Transactions on Geoscience and Remote Sensing.
[39] Raquel Urtasun,et al. Latent Structured Active Learning , 2013, NIPS.
[40] Dino Ienco,et al. Clustering Based Active Learning for Evolving Data Streams , 2013, Discovery Science.
[41] Ahmed K. Elmagarmid,et al. Active Learning With Optimal Instance Subset Selection , 2013, IEEE Transactions on Cybernetics.
[42] Andreas Krause,et al. Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization , 2013, ICML.
[43] Xuelong Li,et al. Hessian Regularized Support Vector Machines for Mobile Image Annotation on the Cloud , 2013, IEEE Transactions on Multimedia.
[44] Nathan Srebro,et al. Active collaborative permutation learning , 2014, KDD.
[45] Jan Kautz,et al. Hierarchical Subquery Evaluation for Active Learning on a Graph , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[46] Chengqi Zhang,et al. Active Learning without Knowing Individual Instance Labels: A Pairwise Label Homogeneity Query Approach , 2014, IEEE Transactions on Knowledge and Data Engineering.
[47] Ling Shao,et al. Weakly-Supervised Cross-Domain Dictionary Learning for Visual Recognition , 2014, International Journal of Computer Vision.
[48] Hao Wu,et al. Double Constrained NMF for Hyperspectral Unmixing , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[49] Ashish Kapoor,et al. Active learning for sparse bayesian multilabel classification , 2014, KDD.
[50] Rong Jin,et al. Active Learning by Querying Informative and Representative Examples , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[51] Ling Shao,et al. A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior , 2015, IEEE Transactions on Image Processing.
[52] Dacheng Tao,et al. Multi-View Intact Space Learning , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[53] Ling Shao,et al. Multiview Alignment Hashing for Efficient Image Search , 2015, IEEE Transactions on Image Processing.
[54] Xindong Wu,et al. Active Learning With Imbalanced Multiple Noisy Labeling , 2015, IEEE Transactions on Cybernetics.
[55] Bo Du,et al. Ensemble manifold regularized sparse low-rank approximation for multiview feature embedding , 2015, Pattern Recognit..
[56] Joel Young,et al. Leveraging In-Batch Annotation Bias for Crowdsourced Active Learning , 2015, WSDM.
[57] Bernhard Sick,et al. Transductive active learning - A new semi-supervised learning approach based on iteratively refined generative models to capture structure in data , 2015, Inf. Sci..
[58] Dacheng Tao,et al. Classification with Noisy Labels by Importance Reweighting , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[59] Ling Shao,et al. Structure-Preserving Binary Representations for RGB-D Action Recognition , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[60] Xuelong Li,et al. Principal Component 2-D Long Short-Term Memory for Font Recognition on Single Chinese Characters , 2016, IEEE Transactions on Cybernetics.
[61] Ling Shao,et al. Unsupervised Local Feature Hashing for Image Similarity Search , 2016, IEEE Transactions on Cybernetics.
[62] Mingli Song,et al. Manifold Ranking-Based Matrix Factorization for Saliency Detection , 2016, IEEE Transactions on Neural Networks and Learning Systems.
[63] Xiaojin Zhu,et al. Semi-Supervised Learning , 2010, Encyclopedia of Machine Learning.