Multi-Modal Distance Metric Learning

@inproceedings{Xie2013MultiModalDM,
  title={Multi-Modal Distance Metric Learning},
  author={Pengtao Xie and Eric P. Xing},
  booktitle={IJCAI},
  year={2013}
}
Multi-modal data is dramatically increasing with the fast growth of social media. Learning a good distance measure for data with multiple modalities is of vital importance for many applications, including retrieval, clustering, classification and recommendation. In this paper, we propose an effective and scalable multi-modal distance metric learning framework. Based on the multi-wing harmonium model, our method provides a principled way to embed data of arbitrary modalities into a single latent… CONTINUE READING

Figures, Tables, and Topics from this paper.

Citations

Publications citing this paper.
SHOWING 1-10 OF 32 CITATIONS

Similarity Gaussian Process Latent Variable Model for Multi-modal Data Analysis

  • 2015 IEEE International Conference on Computer Vision (ICCV)
  • 2015
VIEW 3 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

A Flexible Framework for Projecting Heterogeneous Data

VIEW 4 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

AE2-Nets: Autoencoder in Autoencoder Networks

  • CVPR
  • 2019
VIEW 1 EXCERPT
CITES METHODS

Ensemble Teaching for Hybrid Label Propagation

  • IEEE Transactions on Cybernetics
  • 2019
VIEW 1 EXCERPT
CITES BACKGROUND

Metric Learning on Healthcare Data with Incomplete Modalities

  • IJCAI
  • 2019
VIEW 2 EXCERPTS
CITES METHODS & BACKGROUND

Cross modal similarity learning with active queries

VIEW 3 EXCERPTS
CITES METHODS & BACKGROUND