Fei Sha
Fei Sha
Associate Professor of Computer Science, U. of Southern California
Verified email at usc.edu - Homepage
Cited by
Cited by
Shallow parsing with conditional random fields
F Sha, F Pereira
Proceedings of the 2003 Human Language Technology Conference of the North …, 2003
Geodesic flow kernel for unsupervised domain adaptation
B Gong, Y Shi, F Sha, K Grauman
2012 IEEE Conference on Computer Vision and Pattern Recognition, 2066-2073, 2012
Marginalized denoising autoencoders for domain adaptation
M Chen, Z Xu, K Weinberger, F Sha
arXiv preprint arXiv:1206.4683, 2012
Learning a kernel matrix for nonlinear dimensionality reduction
KQ Weinberger, F Sha, LK Saul
Proceedings of the twenty-first international conference on Machine learning …, 2004
DiscLDA: Discriminative learning for dimensionality reduction and classification
S Lacoste-Julien, F Sha, MI Jordan
Advances in neural information processing systems, 897-904, 2009
Learning globally-consistent local distance functions for shape-based image retrieval and classification
A Frome, Y Singer, F Sha, J Malik
2007 IEEE 11th International Conference on Computer Vision, 1-8, 2007
Synthesized classifiers for zero-shot learning
S Changpinyo, WL Chao, B Gong, F Sha
Proceedings of the IEEE conference on computer vision and pattern …, 2016
Connecting the dots with landmarks: Discriminatively learning domain-invariant features for unsupervised domain adaptation
B Gong, K Grauman, F Sha
International Conference on Machine Learning, 222-230, 2013
Multiplicative updates for nonnegative quadratic programming in support vector machines
F Sha, LK Saul, DD Lee
Advances in neural information processing systems, 1065-1072, 2003
Video summarization with long short-term memory
K Zhang, WL Chao, F Sha, K Grauman
European conference on computer vision, 766-782, 2016
Learning with Whom to Share in Multi-task Feature Learning.
Z Kang, K Grauman, F Sha
ICML 2 (3), 4, 2011
Spectral methods for dimensionality reduction.
LK Saul, KQ Weinberger, F Sha, J Ham, DD Lee
Semi-supervised learning 3, 2006
Diverse sequential subset selection for supervised video summarization
B Gong, WL Chao, K Grauman, F Sha
Advances in neural information processing systems, 2069-2077, 2014
Deformable spatial pyramid matching for fast dense correspondences
J Kim, C Liu, F Sha, K Grauman
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
Large margin hidden Markov models for automatic speech recognition
F Sha, LK Saul
Advances in neural information processing systems, 1249-1256, 2007
An empirical study and analysis of generalized zero-shot learning for object recognition in the wild
WL Chao, S Changpinyo, B Gong, F Sha
European Conference on Computer Vision, 52-68, 2016
Non-linear metric learning
D Kedem, S Tyree, F Sha, GR Lanckriet, KQ Weinberger
Advances in neural information processing systems, 2573-2581, 2012
Large margin Gaussian mixture modeling for phonetic classification and recognition
F Sha, LK Saul
2006 IEEE International Conference on Acoustics Speech and Signal Processing …, 2006
Information-theoretical learning of discriminative clusters for unsupervised domain adaptation
Y Shi, F Sha
arXiv preprint arXiv:1206.6438, 2012
Graph Laplacian regularization for large-scale semidefinite programming
KQ Weinberger, F Sha, Q Zhu, LK Saul
Advances in neural information processing systems, 1489-1496, 2007
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