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Robust metric learning by smooth optimization

Publication ,  Conference
Huang, K; Jin, R; Xu, Z; Liu, CL
Published in: Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010
January 1, 2010

Most existing distance metric learning methods assume perfect side information that is usually given in pairwise or triplet constraints. Instead, in many real-world applications, the constraints are derived from side information, such as users' implicit feedbacks and citations among articles. As a result, these constraints are usually noisy and contain many mistakes. In this work, we aim to learn a distance metric from noisy constraints by robust optimization in a worst-case scenario, to which we refer as robust metric learning. We formulate the learning task initially as a combinatorial optimization problem, and show that it can be elegantly transformed to a convex programming problem. We present an efficient learning algorithm based on smooth optimization [7]. It has a worst-case convergence rate of O(1/ √ ε) for smooth optimization problems, where ε is the desired error of the approximate solution. Finally, our empirical study with UCI data sets demonstrate the effectiveness of the proposed method in comparison to state-of-the-art methods.

Duke Scholars

Published In

Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010

ISBN

9780974903965

Publication Date

January 1, 2010

Start / End Page

244 / 251
 

Citation

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Huang, K., Jin, R., Xu, Z., & Liu, C. L. (2010). Robust metric learning by smooth optimization. In Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010 (pp. 244–251).
Huang, K., R. Jin, Z. Xu, and C. L. Liu. “Robust metric learning by smooth optimization.” In Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010, 244–51, 2010.
Huang K, Jin R, Xu Z, Liu CL. Robust metric learning by smooth optimization. In: Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010. 2010. p. 244–51.
Huang, K., et al. “Robust metric learning by smooth optimization.” Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010, 2010, pp. 244–51.
Huang K, Jin R, Xu Z, Liu CL. Robust metric learning by smooth optimization. Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010. 2010. p. 244–251.

Published In

Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010

ISBN

9780974903965

Publication Date

January 1, 2010

Start / End Page

244 / 251