-
1
-
-
77956031473
-
A survey on transfer learning
-
S. J. Pan and Q. Yang. A survey on transfer learning. TKDE, 22(10):1345-1359, 2010.
-
(2010)
TKDE
, vol.22
, Issue.10
, pp. 1345-1359
-
-
Pan, S.J.1
Yang, Q.2
-
2
-
-
84919881041
-
Decaf: A deep convolutional activation feature for generic visual recognition
-
J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell. Decaf: A deep convolutional activation feature for generic visual recognition. In ICML, 2014.
-
(2014)
ICML
-
-
Donahue, J.1
Jia, Y.2
Vinyals, O.3
Hoffman, J.4
Zhang, N.5
Tzeng, E.6
Darrell, T.7
-
3
-
-
84937508363
-
How transferable are features in deep neural networks?
-
J. Yosinski, J. Clune, Y. Bengio, and H. Lipson. How transferable are features in deep neural networks? In NIPS, 2014.
-
(2014)
NIPS
-
-
Yosinski, J.1
Clune, J.2
Bengio, Y.3
Lipson, H.4
-
5
-
-
84969549144
-
Learning transferable features with deep adaptation networks
-
M. Long, Y. Cao, J. Wang, and M. I. Jordan. Learning transferable features with deep adaptation networks. In ICML, 2015.
-
(2015)
ICML
-
-
Long, M.1
Cao, Y.2
Wang, J.3
Jordan, M.I.4
-
6
-
-
84969802531
-
Unsupervised domain adaptation by backpropagation
-
Y. Ganin and V. Lempitsky. Unsupervised domain adaptation by backpropagation. In ICML, 2015.
-
(2015)
ICML
-
-
Ganin, Y.1
Lempitsky, V.2
-
7
-
-
84973897613
-
Simultaneous deep transfer across domains and tasks
-
E. Tzeng, J. Hoffman, N. Zhang, K. Saenko, and T. Darrell. Simultaneous deep transfer across domains and tasks. In ICCV, 2015.
-
(2015)
ICCV
-
-
Tzeng, E.1
Hoffman, J.2
Zhang, N.3
Saenko, K.4
Darrell, T.5
-
8
-
-
84986274465
-
Deep residual learning for image recognition
-
K. He, X. Zhang, S. Ren, and J. Sun. Deep residual learning for image recognition. In CVPR, 2016.
-
(2016)
CVPR
-
-
He, K.1
Zhang, X.2
Ren, S.3
Sun, J.4
-
9
-
-
79951681949
-
Domain adaptation via transfer component analysis
-
S. J. Pan, I. W. Tsang, J. T. Kwok, and Q. Yang. Domain adaptation via transfer component analysis. TNNLS, 22(2):199-210, 2011.
-
(2011)
TNNLS
, vol.22
, Issue.2
, pp. 199-210
-
-
Pan, S.J.1
Tsang, I.W.2
Kwok, J.T.3
Yang, Q.4
-
10
-
-
84863393661
-
Domain transfer multiple kernel learning
-
L. Duan, I. W. Tsang, and D. Xu. Domain transfer multiple kernel learning. TPAMI, 34(3):465-479, 2012.
-
(2012)
TPAMI
, vol.34
, Issue.3
, pp. 465-479
-
-
Duan, L.1
Tsang, I.W.2
Xu, D.3
-
12
-
-
84937915474
-
Flexible transfer learning under support and model shift
-
X. Wang and J. Schneider. Flexible transfer learning under support and model shift. In NIPS, 2014.
-
(2014)
NIPS
-
-
Wang, X.1
Schneider, J.2
-
14
-
-
84866657270
-
Geodesic flow kernel for unsupervised domain adaptation
-
B. Gong, Y. Shi, F. Sha, and K. Grauman. Geodesic flow kernel for unsupervised domain adaptation. In CVPR, 2012.
-
(2012)
CVPR
-
-
Gong, B.1
Shi, Y.2
Sha, F.3
Grauman, K.4
-
15
-
-
84924803045
-
LSDA: Large scale detection through adaptation
-
J. Hoffman, S. Guadarrama, E. Tzeng, R. Hu, J. Donahue, R. Girshick, T. Darrell, and K. Saenko. LSDA: Large scale detection through adaptation. In NIPS, 2014.
-
(2014)
NIPS
-
-
Hoffman, J.1
Guadarrama, S.2
Tzeng, E.3
Hu, R.4
Donahue, J.5
Girshick, R.6
Darrell, T.7
Saenko, K.8
-
16
-
-
80053558787
-
Natural language processing (almost) from scratch
-
R. Collobert, J. Weston, L. Bottou, M. Karlen, K. Kavukcuoglu, and P. Kuksa. Natural language processing (almost) from scratch. JMLR, 12:2493-2537, 2011.
-
(2011)
JMLR
, vol.12
, pp. 2493-2537
-
-
Collobert, R.1
Weston, J.2
Bottou, L.3
Karlen, M.4
Kavukcuoglu, K.5
Kuksa, P.6
-
17
-
-
84879854889
-
Representation learning: A review and new perspectives
-
Y. Bengio, A. Courville, and P. Vincent. Representation learning: A review and new perspectives. TPAMI, 35(8):1798-1828, 2013.
-
(2013)
TPAMI
, vol.35
, Issue.8
, pp. 1798-1828
-
-
Bengio, Y.1
Courville, A.2
Vincent, P.3
-
18
-
-
80053443013
-
Domain adaptation for large-scale sentiment classification: A deep learning approach
-
X. Glorot, A. Bordes, and Y. Bengio. Domain adaptation for large-scale sentiment classification: A deep learning approach. In ICML, 2011.
-
(2011)
ICML
-
-
Glorot, X.1
Bordes, A.2
Bengio, Y.3
-
19
-
-
84908539410
-
Learning and transferring mid-level image representations using convolutional neural networks
-
June
-
M. Oquab, L. Bottou, I. Laptev, and J. Sivic. Learning and transferring mid-level image representations using convolutional neural networks. In CVPR, June 2013.
-
(2013)
CVPR
-
-
Oquab, M.1
Bottou, L.2
Laptev, I.3
Sivic, J.4
-
20
-
-
80053437179
-
Multimodal deep learning
-
J. Ngiam, A. Khosla, M. Kim, J. Nam, H. Lee, and A. Y. Ng. Multimodal deep learning. In ICML, 2011.
-
(2011)
ICML
-
-
Ngiam, J.1
Khosla, A.2
Kim, M.3
Nam, J.4
Lee, H.5
Ng, A.Y.6
-
21
-
-
84898072330
-
Domain adaptation: Learning bounds and algorithms
-
Y. Mansour, M. Mohri, and A. Rostamizadeh. Domain adaptation: Learning bounds and algorithms. In COLT, 2009.
-
(2009)
COLT
-
-
Mansour, Y.1
Mohri, M.2
Rostamizadeh, A.3
-
22
-
-
84897573740
-
A theory of learning from different domains
-
S. Ben-David, J. Blitzer, K. Crammer, A. Kulesza, F. Pereira, and J. W. Vaughan. A theory of learning from different domains. MLJ, 79(1-2):151-175, 2010.
-
(2010)
MLJ
, vol.79
, Issue.1-2
, pp. 151-175
-
-
Ben-David, S.1
Blitzer, J.2
Crammer, K.3
Kulesza, A.4
Pereira, F.5
Vaughan, J.W.6
-
23
-
-
37849026107
-
Cross-domain video concept detection using adaptive svms
-
ACM
-
J. Yang, R. Yan, and A. G. Hauptmann. Cross-domain video concept detection using adaptive svms. In MM, pages 188-197. ACM, 2007.
-
(2007)
MM
, pp. 188-197
-
-
Yang, J.1
Yan, R.2
Hauptmann, A.G.3
-
24
-
-
79953064532
-
Domain adaptation from multiple sources via auxiliary classifiers
-
ACM
-
Lixin Duan, Ivor W Tsang, Dong Xu, and Tat-Seng Chua. Domain adaptation from multiple sources via auxiliary classifiers. In ICML, pages 289-296. ACM, 2009.
-
(2009)
ICML
, pp. 289-296
-
-
Duan, L.1
Tsang, I.W.2
Xu, D.3
Tat, S.-C.4
-
25
-
-
84865579385
-
Visual event recognition in videos by learning from web data
-
L. Duan, D. Xu, I. W. Tsang, and J. Luo. Visual event recognition in videos by learning from web data. TPAMI, 34(9):1667-1680, 2012.
-
(2012)
TPAMI
, vol.34
, Issue.9
, pp. 1667-1680
-
-
Duan, L.1
Xu, D.2
Tsang, I.W.3
Luo, J.4
-
26
-
-
84876231242
-
Imagenet classification with deep convolutional neural networks
-
A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 2012.
-
(2012)
NIPS
-
-
Krizhevsky, A.1
Sutskever, I.2
Hinton, G.E.3
-
27
-
-
84859477054
-
A kernel two-sample test
-
March
-
A. Gretton, K. Borgwardt, M. Rasch, B. Schölkopf, and A. Smola. A kernel two-sample test. JMLR, 13:723-773, March 2012.
-
(2012)
JMLR
, vol.13
, pp. 723-773
-
-
Gretton, A.1
Borgwardt, K.2
Rasch, M.3
Schölkopf, B.4
Smola, A.5
-
28
-
-
29344448013
-
Semi-supervised learning by entropy minimization
-
Y. Grandvalet and Y. Bengio. Semi-supervised learning by entropy minimization. In NIPS, 2004.
-
(2004)
NIPS
-
-
Grandvalet, Y.1
Bengio, Y.2
-
29
-
-
84973863234
-
Bilinear cnn models for fine-grained visual recognition
-
Tsung-Yu Lin, Aruni RoyChowdhury, and Subhransu Maji. Bilinear cnn models for fine-grained visual recognition. In CVPR, pages 1449-1457, 2015.
-
(2015)
CVPR
, pp. 1449-1457
-
-
Tsung, Y.-L.1
RoyChowdhury, A.2
Maji, S.3
-
30
-
-
84990048974
-
Return of frustratingly easy domain adaptation
-
B. Sun, J. Feng, and K. Saenko. Return of frustratingly easy domain adaptation. In AAAI, 2016.
-
(2016)
AAAI
-
-
Sun, B.1
Feng, J.2
Saenko, K.3
-
31
-
-
80052908300
-
Unbiased look at dataset bias
-
A. Torralba and A. A. Efros. Unbiased look at dataset bias. In CVPR, 2011.
-
(2011)
CVPR
-
-
Torralba, A.1
Efros, A.A.2
|