-
2
-
-
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, David JC1
-
6
-
-
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 IEEE International Conference on Computer Vision, pages 209-216, 2013.
-
(2013)
IEEE International Conference on Computer Vision
, pp. 209-216
-
-
Elhamifar, Ehsan1
Sapiro, Guillermo2
Yang, Allen3
Shankar Sasrty, S4
-
8
-
-
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, Yi1
Ma, Zhigang2
Nie, Feiping3
Chang, Xiaojun4
Hauptmann, Alexander G5
-
14
-
-
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, Daniel1
Krause, Andreas2
-
16
-
-
84986274465
-
Deep residual learning for image recognition
-
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Deep residual learning for image recognition. In IEEE Conference on Computer Vision and Pattern Recognition, pages 770-778, 2016.
-
(2016)
IEEE Conference on Computer Vision and Pattern Recognition
, pp. 770-778
-
-
He, Kaiming1
Zhang, Xiangyu2
Ren, Shaoqing3
Sun, Jian4
-
17
-
-
3042813990
-
Fisher information inequalities and the central limit theorem
-
Oliver Johnson and Andrew Barron. Fisher information inequalities and the central limit theorem. Probability Theory and Related Fields, 129(3):391-409, 2004.
-
(2004)
Probability Theory and Related Fields
, vol.129
, Issue.3
, pp. 391-409
-
-
Johnson, Oliver1
Barron, Andrew2
-
18
-
-
85067571627
-
Deep kernel learning
-
Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, and Eric P Xing. Deep kernel learning. In Artificial Intelligence and Statistics, pages 370-378, 2016.
-
(2016)
Artificial Intelligence and Statistics
, pp. 370-378
-
-
Wilson, Andrew Gordon1
Hu, Zhiting2
Salakhutdinov, Ruslan3
Xing, Eric P4
-
20
-
-
84873435224
-
Fast approximation of matrix coherence and statistical leverage
-
Petros Drineas, Malik Magdon-Ismail, Michael W Mahoney, and David P Woodruff. Fast approximation of matrix coherence and statistical leverage. Journal of Machine Learning Research, 13(Dec):3475-3506, 2012.
-
(2012)
Journal of Machine Learning Research
, vol.13
, Issue.Dec
, pp. 3475-3506
-
-
Drineas, Petros1
Magdon-Ismail, Malik2
Mahoney, Michael W3
Woodruff, David P4
-
21
-
-
84938311437
-
A statistical perspective on algorithmic leveraging
-
Ping Ma, Michael W Mahoney, and Bin Yu. A statistical perspective on algorithmic leveraging. The Journal of Machine Learning Research, 16(1):861-911, 2015.
-
(2015)
The Journal of Machine Learning Research
, vol.16
, Issue.1
, pp. 861-911
-
-
Ma, Ping1
Mahoney, Michael W2
Yu, Bin3
-
23
-
-
0000023163
-
Tables for computing bivariate normal probabilities
-
Donald B Owen. Tables for computing bivariate normal probabilities. The Annals of Mathematical Statistics, 27(4):1075-1090, 1956.
-
(1956)
The Annals of Mathematical Statistics
, vol.27
, Issue.4
, pp. 1075-1090
-
-
Owen, Donald B1
-
26
-
-
34250745927
-
Batch mode active learning and its application to medical image classification
-
Steven CH Hoi, Rong Jin, Jianke Zhu, and Michael R Lyu. Batch mode active learning and its application to medical image classification. In International Conference on Machine Learning, pages 417-424, 2006.
-
(2006)
International Conference on Machine Learning
, pp. 417-424
-
-
Hoi, Steven CH1
Jin, Rong2
Zhu, Jianke3
Lyu, Michael R4
-
30
-
-
84965123646
-
Parallel predictive entropy search for batch global optimization of expensive objective functions
-
Amar Shah and Zoubin Ghahramani. Parallel predictive entropy search for batch global optimization of expensive objective functions. In Advances in Neural Information Processing Systems, pages 3330-3338, 2015.
-
(2015)
Advances in Neural Information Processing Systems
, pp. 3330-3338
-
-
Shah, Amar1
Ghahramani, Zoubin2
-
32
-
-
84886572732
-
Parallel gaussian process optimization with upper confidence bound and pure exploration
-
Emile Contal, David Buffoni, Alexandre Robicquet, and Nicolas Vayatis. Parallel gaussian process optimization with upper confidence bound and pure exploration. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pages 225-240, 2013.
-
(2013)
Joint European Conference on Machine Learning and Knowledge Discovery in Databases
, pp. 225-240
-
-
Contal, Emile1
Buffoni, David2
Robicquet, Alexandre3
Vayatis, Nicolas4
-
33
-
-
84942597150
-
Parallelizing exploration-exploitation tradeoffs in gaussian process bandit optimization
-
Thomas Desautels, Andreas Krause, and Joel W Burdick. Parallelizing exploration-exploitation tradeoffs in gaussian process bandit optimization. The Journal of Machine Learning Research, 15(1):3873-3923, 2014.
-
(2014)
The Journal of Machine Learning Research
, vol.15
, Issue.1
, pp. 3873-3923
-
-
Desautels, Thomas1
Krause, Andreas2
Burdick, Joel W3
-
34
-
-
85030677529
-
Batch Bayesian optimization via local penalization
-
Javier González, Zhenwen Dai, Philipp Hennig, and Neil Lawrence. Batch Bayesian optimization via local penalization. In Artificial Intelligence and Statistics, pages 648-657, 2016.
-
(2016)
Artificial Intelligence and Statistics
, pp. 648-657
-
-
González, Javier1
Dai, Zhenwen2
Hennig, Philipp3
Lawrence, Neil4
-
35
-
-
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 IEEE International Conference on Computer Vision, pages 1-8, 2007.
-
(2007)
IEEE International Conference on Computer Vision
, pp. 1-8
-
-
Kapoor, Ashish1
Grauman, Kristen2
Urtasun, Raquel3
Darrell, Trevor4
-
37
-
-
65749118363
-
Graphical models, exponential families, and variational inference
-
Martin J Wainwright, Michael I Jordan, et al. Graphical models, exponential families, and variational inference. Foundations and Trends™ in Machine Learning, 1(1-2):1-305, 2008.
-
(2008)
Foundations and Trends™ in Machine Learning
, vol.1
, Issue.1-2
, pp. 1-305
-
-
Wainwright, Martin J1
Jordan, Michael I2
|