-
1
-
-
84958264664
-
-
Martin Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al. Tensorflow: Large-scale machine learning on heterogeneous distributed systems. arXiv:1603.04467, 2016.
-
(2016)
Tensorflow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
-
-
Abadi, M.1
Agarwal, A.2
Barham, P.3
Brevdo, E.4
Chen, Z.5
Citro, C.6
Corrado, G.S.7
Davis, A.8
Dean, J.9
Devin, M.10
-
2
-
-
84969939978
-
Active nearest neighbors in changing environments
-
C. Berlind and R. Urner. Active nearest neighbors in changing environments. In ICML, 2015.
-
(2015)
ICML
-
-
Berlind, C.1
Urner, R.2
-
3
-
-
1942517333
-
Incorporating diversity in active learning with support vector machines
-
Klaus Brinker. Incorporating diversity in active learning with support vector machines. In ICML, volume 3, pp. 59–66, 2003.
-
(2003)
ICML
, vol.3
, pp. 59-66
-
-
Brinker, K.1
-
4
-
-
0004054088
-
-
Springer
-
William J Cook, William H Cunningham, William R Pulleyblank, and Alexander Schrijver. Combinatorial optimization, volume 605. Springer, 1998.
-
(1998)
Combinatorial Optimization
, vol.605
-
-
Cook, W.J.1
Cunningham, W.H.2
Pulleyblank, W.R.3
Schrijver, A.4
-
5
-
-
33749257223
-
Analysis of a greedy active learning strategy
-
Sanjoy Dasgupta. Analysis of a greedy active learning strategy. In NIPS, 2004.
-
(2004)
NIPS
-
-
Dasgupta, S.1
-
6
-
-
84898947320
-
Analysis of a greedy active learning strategy
-
L. K. Saul, Y. Weiss, and L. Bottou (eds, MIT Press
-
Sanjoy Dasgupta. Analysis of a greedy active learning strategy. In L. K. Saul, Y. Weiss, and L. Bottou (eds.), Advances in Neural Information Processing Systems 17, pp. 337–344. MIT Press, 2005. URL http://papers.nips.cc/paper/2636-analysis-of-a-greedy-active-learning-strategy.pdf.
-
(2005)
Advances in Neural Information Processing Systems
, vol.17
, pp. 337-344
-
-
Dasgupta, S.1
-
7
-
-
79952041537
-
Batch-mode active-learning methods for the interactive classification of remote sensing images
-
Begüm Demir, Claudio Persello, and Lorenzo Bruzzone. Batch-mode active-learning methods for the interactive classification of remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 49(3):1014–1031, 2011.
-
(2011)
IEEE Transactions on Geoscience and Remote Sensing
, vol.49
, Issue.3
, pp. 1014-1031
-
-
Demir, B.1
Persello, C.2
Bruzzone, L.3
-
9
-
-
85018872904
-
-
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martin Arjovsky, Olivier Mastropietro, and Aaron Courville. Adversarially learned inference. arXiv:1606.00704, 2016.
-
(2016)
Adversarially Learned Inference
-
-
Dumoulin, V.1
Belghazi, I.2
Poole, B.3
Lamb, A.4
Arjovsky, M.5
Mastropietro, O.6
Courville, A.7
-
10
-
-
84898808985
-
A convex optimization framework for active learning
-
Ehsan Elhamifar, Guillermo Sapiro, Allen Yang, and S Shankar Sasrty. A convex optimization framework for active learning. In ICCV, 2013.
-
(2013)
ICCV
-
-
Elhamifar, E.1
Sapiro, G.2
Yang, A.3
Sasrty, S.S.4
-
11
-
-
0031209604
-
Selective sampling using the query by committee algorithm
-
Yoav Freund, H Sebastian Seung, Eli Shamir, and Naftali Tishby. Selective sampling using the query by committee algorithm. Machine learning, 28(2-3), 1997.
-
(1997)
Machine Learning
, vol.28
, Issue.2-3
-
-
Freund, Y.1
Seung, H.S.2
Shamir, E.3
Tishby, N.4
-
12
-
-
84998879817
-
Dropout as a Bayesian approximation: Representing model uncertainty in deep learning
-
Yarin Gal and Zoubin Ghahramani. Dropout as a bayesian approximation: Representing model uncertainty in deep learning. In International Conference on Machine Learning, 2016.
-
(2016)
International Conference on Machine Learning
-
-
Gal, Y.1
Ghahramani, Z.2
-
15
-
-
84856462978
-
Adaptive submodularity: Theory and applications in active learning and stochastic optimization
-
Daniel Golovin and Andreas Krause. Adaptive submodularity: Theory and applications in active learning and stochastic optimization. Journal of Artificial Intelligence Research, 42:427–486, 2011.
-
(2011)
Journal of Artificial Intelligence Research
, vol.42
, pp. 427-486
-
-
Golovin, D.1
Krause, A.2
-
16
-
-
84885625669
-
Efficient active learning of halfspaces: An aggressive approach
-
Alon Gonen, Sivan Sabato, and Shai Shalev-Shwartz. Efficient active learning of halfspaces: an aggressive approach. The Journal of Machine Learning Research, 14(1):2583–2615, 2013.
-
(2013)
The Journal of Machine Learning Research
, vol.14
, Issue.1
, pp. 2583-2615
-
-
Gonen, A.1
Sabato, S.2
Shalev-Shwartz, S.3
-
17
-
-
84937849144
-
Generative adversarial nets
-
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. Generative adversarial nets. In NIPS, 2014.
-
(2014)
NIPS
-
-
Goodfellow, I.1
Pouget-Abadie, J.2
Mirza, M.3
Xu, B.4
Warde-Farley, D.5
Ozair, S.6
Courville, A.7
Bengio, Y.8
-
24
-
-
84986274465
-
Deep residual learning for image recognition
-
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 770–778, 2016.
-
(2016)
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
, pp. 770-778
-
-
He, K.1
Zhang, X.2
Ren, S.3
Sun, J.4
-
25
-
-
34250745927
-
Batch mode active learning and its application to medical image classification
-
ACM
-
Steven CH Hoi, Rong Jin, Jianke Zhu, and Michael R Lyu. Batch mode active learning and its application to medical image classification. In Proceedings of the 23rd international conference on Machine learning, pp. 417–424. ACM, 2006.
-
(2006)
Proceedings of the 23rd International Conference on Machine Learning
, pp. 417-424
-
-
Hoi, S.C.H.1
Jin, R.2
Zhu, J.3
Lyu, M.R.4
-
27
-
-
70450181250
-
Multi-class active learning for image classification
-
Ajay J Joshi, Fatih Porikli, and Nikolaos Papanikolopoulos. Multi-class active learning for image classification. In CVPR, 2009.
-
(2009)
CVPR
-
-
Joshi, A.J.1
Porikli, F.2
Papanikolopoulos, N.3
-
29
-
-
50649102302
-
Active learning with Gaussian processes for object categorization
-
Ashish Kapoor, Kristen Grauman, Raquel Urtasun, and Trevor Darrell. Active learning with gaussian processes for object categorization. In ICCV, 2007.
-
(2007)
ICCV
-
-
Kapoor, A.1
Grauman, K.2
Urtasun, R.3
Darrell, T.4
-
31
-
-
84887354642
-
Adaptive active learning for image classification
-
Xin Li and Yuhong Guo. Adaptive active learning for image classification. In CVPR, 2013.
-
(2013)
CVPR
-
-
Li, X.1
Guo, Y.2
-
33
-
-
0000695404
-
Information-based objective functions for active data selection
-
David JC MacKay. Information-based objective functions for active data selection. Neural computation, 4(4):590–604, 1992.
-
(1992)
Neural Computation
, vol.4
, Issue.4
, pp. 590-604
-
-
MacKay, D.J.C.1
-
34
-
-
0002332781
-
Employing em and pool-based active learning for text classification
-
Andrew Kachites McCallumzy and Kamal Nigamy. Employing em and pool-based active learning for text classification. In ICML, 1998.
-
(1998)
ICML
-
-
McCallumzy, A.K.1
Nigamy, K.2
-
35
-
-
84865114495
-
Reading digits in natural images with unsupervised feature learning
-
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y Ng. Reading digits in natural images with unsupervised feature learning. In NIPS workshop on deep learning and unsupervised feature learning, volume 2011, pp. 5, 2011.
-
(2011)
NIPS Workshop on Deep Learning and Unsupervised Feature Learning
, vol.2011
, pp. 5
-
-
Netzer, Y.1
Wang, T.2
Coates, A.3
Bissacco, A.4
Wu, B.5
Ng, A.Y.6
-
37
-
-
84965136229
-
Semi-supervised learning with ladder networks
-
Antti Rasmus, Mathias Berglund, Mikko Honkala, Harri Valpola, and Tapani Raiko. Semi-supervised learning with ladder networks. In NIPS, 2015.
-
(2015)
NIPS
-
-
Rasmus, A.1
Berglund, M.2
Honkala, M.3
Valpola, H.4
Raiko, T.5
-
38
-
-
0442319140
-
Toward optimal active learning through monte carlo estimation of error reduction
-
Nicholas Roy and Andrew McCallum. Toward optimal active learning through monte carlo estimation of error reduction. ICML, 2001.
-
(2001)
ICML
-
-
Roy, N.1
McCallum, A.2
-
39
-
-
85018875486
-
Improved techniques for training gans
-
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen. Improved techniques for training gans. In NIPS, 2016.
-
(2016)
NIPS
-
-
Salimans, T.1
Goodfellow, I.2
Zaremba, W.3
Cheung, V.4
Radford, A.5
Chen, X.6
-
40
-
-
68949137209
-
-
University of Wisconsin, Madison
-
Burr Settles. Active learning literature survey. University of Wisconsin, Madison, 52(55-66):11, 2010.
-
(2010)
Active Learning Literature Survey
, vol.52
, Issue.55-66
, pp. 11
-
-
Settles, B.1
-
43
-
-
0042868698
-
Support vector machine active learning with applications to text classification
-
Simon Tong and Daphne Koller. Support vector machine active learning with applications to text classification. JMLR, 2(Nov):45–66, 2001.
-
(2001)
JMLR
, vol.2
, Issue.Nov
, pp. 45-66
-
-
Tong, S.1
Koller, D.2
-
44
-
-
21844440579
-
Core vector machines: Fast SVM training on very large data sets
-
Ivor W Tsang, James T Kwok, and Pak-Ming Cheung. Core vector machines: Fast svm training on very large data sets. JMLR, 6(Apr):363–392, 2005.
-
(2005)
JMLR
, vol.6
, Issue.Apr
, pp. 363-392
-
-
Tsang, I.W.1
Kwok, J.T.2
Cheung, P.-M.3
-
45
-
-
85015304982
-
Cost-effective active learning for deep image classification
-
Keze Wang, Dongyu Zhang, Ya Li, Ruimao Zhang, and Liang Lin. Cost-effective active learning for deep image classification. Transactions on Circuits and Systems for Video Technology, 2016.
-
(2016)
Transactions on Circuits and Systems for Video Technology
-
-
Wang, K.1
Zhang, D.2
Li, Y.3
Zhang, R.4
Lin, L.5
-
46
-
-
84923696228
-
Querying discriminative and representative samples for batch mode active learning
-
Zheng Wang and Jieping Ye. Querying discriminative and representative samples for batch mode active learning. ACM Transactions on Knowledge Discovery from Data (TKDD), 9(3):17, 2015.
-
(2015)
ACM Transactions on Knowledge Discovery from Data (TKDD)
, vol.9
, Issue.3
, pp. 17
-
-
Wang, Z.1
Ye, J.2
-
47
-
-
84926184611
-
Using document summarization techniques for speech data subset selection
-
Kai Wei, Yuzong Liu, Katrin Kirchhoff, and Jeff A Bilmes. Using document summarization techniques for speech data subset selection. In HLT-NAACL, 2013.
-
(2013)
HLT-NAACL
-
-
Wei, K.1
Liu, Y.2
Kirchhoff, K.3
Bilmes, J.A.4
-
48
-
-
84969930783
-
Submodularity in data subset selection and active learning
-
Kai Wei, Rishabh K Iyer, and Jeff A Bilmes. Submodularity in data subset selection and active learning. In ICML, 2015.
-
(2015)
ICML
-
-
Wei, K.1
Iyer, R.K.2
Bilmes, J.A.3
-
50
-
-
84867738590
-
Robustness and generalization
-
Huan Xu and Shie Mannor. Robustness and generalization. Machine learning, 86(3):391–423, 2012.
-
(2012)
Machine Learning
, vol.86
, Issue.3
, pp. 391-423
-
-
Xu, H.1
Mannor, S.2
-
51
-
-
84940005208
-
Multi-class active learning by uncertainty sampling with diversity maximization
-
Yi Yang, Zhigang Ma, Feiping Nie, Xiaojun Chang, and Alexander G Hauptmann. Multi-class active learning by uncertainty sampling with diversity maximization. International Journal of Computer Vision, 113(2):113–127, 2015.
-
(2015)
International Journal of Computer Vision
, vol.113
, Issue.2
, pp. 113-127
-
-
Yang, Y.1
Ma, Z.2
Nie, F.3
Chang, X.4
Hauptmann, A.G.5
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