Active Learning for Convolutional Neural Networks: A Core-Set Approach
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[1] David J. C. MacKay,et al. Information-Based Objective Functions for Active Data Selection , 1992, Neural Computation.
[2] Andrew McCallum,et al. Employing EM and Pool-Based Active Learning for Text Classification , 1998, ICML.
[3] Daphne Koller,et al. Support Vector Machine Active Learning with Applications to Text Classification , 2002, J. Mach. Learn. Res..
[4] Andrew McCallum,et al. Toward Optimal Active Learning through Monte Carlo Estimation of Error Reduction , 2001, ICML 2001.
[5] Klaus Brinker,et al. Incorporating Diversity in Active Learning with Support Vector Machines , 2003, ICML.
[6] H. Sebastian Seung,et al. Selective Sampling Using the Query by Committee Algorithm , 1997, Machine Learning.
[7] Sanjoy Dasgupta,et al. Analysis of a greedy active learning strategy , 2004, NIPS.
[8] Sariel Har-Peled,et al. Smaller Coresets for k-Median and k-Means Clustering , 2005, SCG.
[9] Ivor W. Tsang,et al. Core Vector Machines: Fast SVM Training on Very Large Data Sets , 2005, J. Mach. Learn. Res..
[10] Rong Jin,et al. Batch mode active learning and its application to medical image classification , 2006, ICML.
[11] Jinbo Bi,et al. Active learning via transductive experimental design , 2006, ICML.
[12] G. Griffin,et al. Caltech-256 Object Category Dataset , 2007 .
[13] Trevor Darrell,et al. Active Learning with Gaussian Processes for Object Categorization , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[14] Dale Schuurmans,et al. Discriminative Batch Mode Active Learning , 2007, NIPS.
[15] Steve Hanneke,et al. A bound on the label complexity of agnostic active learning , 2007, ICML '07.
[16] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[17] Nikolaos Papanikolopoulos,et al. Multi-class active learning for image classification , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[18] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[19] Burr Settles,et al. Active Learning Literature Survey , 2009 .
[20] Nikolaos Papanikolopoulos,et al. Multi-class batch-mode active learning for image classification , 2010, 2010 IEEE International Conference on Robotics and Automation.
[21] Jeff A. Bilmes,et al. Interactive Submodular Set Cover , 2010, ICML.
[22] Yuhong Guo,et al. Active Instance Sampling via Matrix Partition , 2010, NIPS.
[23] Andrew Y. Ng,et al. Reading Digits in Natural Images with Unsupervised Feature Learning , 2011 .
[24] Shie Mannor,et al. Robustness and generalization , 2010, Machine Learning.
[25] Andreas Krause,et al. Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization , 2010, J. Artif. Intell. Res..
[26] Lorenzo Bruzzone,et al. Batch-Mode Active-Learning Methods for the Interactive Classification of Remote Sensing Images , 2011, IEEE Transactions on Geoscience and Remote Sensing.
[27] Alexander G. Gray,et al. UPAL: Unbiased Pool Based Active Learning , 2011, AISTATS.
[28] Xin Li,et al. Adaptive Active Learning for Image Classification , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[29] Shai Shalev-Shwartz,et al. Efficient active learning of halfspaces: an aggressive approach , 2012, J. Mach. Learn. Res..
[30] Jieping Ye,et al. Querying discriminative and representative samples for batch mode active learning , 2013, KDD.
[31] Allen Y. Yang,et al. A Convex Optimization Framework for Active Learning , 2013, 2013 IEEE International Conference on Computer Vision.
[32] Jeff A. Bilmes,et al. Using Document Summarization Techniques for Speech Data Subset Selection , 2013, NAACL.
[33] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[34] Yi Yang,et al. Multi-Class Active Learning by Uncertainty Sampling with Diversity Maximization , 2015, International Journal of Computer Vision.
[35] Tapani Raiko,et al. Semi-supervised Learning with Ladder Networks , 2015, NIPS.
[36] Daniel Cremers,et al. CAPTCHA Recognition with Active Deep Learning , 2015 .
[37] Rishabh K. Iyer,et al. Submodularity in Data Subset Selection and Active Learning , 2015, ICML.
[38] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[39] Ruth Urner,et al. Active Nearest Neighbors in Changing Environments , 2015, ICML.
[40] Franziska Abend,et al. Facility Location Concepts Models Algorithms And Case Studies , 2016 .
[41] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[42] Wojciech Zaremba,et al. Improved Techniques for Training GANs , 2016, NIPS.
[43] Soumith Chintala,et al. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , 2015, ICLR.
[44] Yonatan Wexler,et al. Minimizing the Maximal Loss: How and Why , 2016, ICML.
[45] Martín Abadi,et al. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems , 2016, ArXiv.
[46] Zoubin Ghahramani,et al. Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning , 2015, ICML.
[47] Ruimao Zhang,et al. Cost-Effective Active Learning for Deep Image Classification , 2017, IEEE Transactions on Circuits and Systems for Video Technology.
[48] Zoubin Ghahramani,et al. Deep Bayesian Active Learning with Image Data , 2017, ICML.