Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding

Ma, Xudong; Luo, Ping; Zhuang, Fuzhen; He, Qing; Shi, Zhongzhi; Shen, Zhiyong

doi:10.5591/978-1-57735-516-8/IJCAI11-236

Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding

Xudong Ma, Ping Luo, Fuzhen Zhuang, Qing He, Zhongzhi Shi, Zhiyong Shen

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 1396-1400.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-236

Abstract

Ensemble learning with output from multiple supervised and unsupervised models aims to improvethe classification accuracy of supervised model ensembleby jointly considering the grouping results from unsupervised models. In this paper we cast this ensemble task as an unconstrained probabilistic embedding problem. Specifically, we assume both objects and classes/clusters have latent coordinates without constraints in a D-dimensional Euclidean space, and consider the mapping from the embedded space into the space of results from supervised and unsupervised models as a probabilistic generative process. The prediction of an objectis then determined by the distances between the objectand the classes in the embedded space. A solution of this embedding can be obtained using the quasi-Newton method, resulting in the objects and classes/clusters with high co-occurrence weights being embedded close. We demonstrate the benefits of this unconstrained embedding method by three real applications.

Xudong Ma, Ping Luo, Fuzhen Zhuang, Qing He, Zhongzhi Shi, and Zhiyong Shen. 2011. Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 1396–1400. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-236

@inproceedings{ijcai2011p236,
  title     = {Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding},
  author    = {Ma, Xudong and Luo, Ping and Zhuang, Fuzhen and He, Qing and Shi, Zhongzhi and Shen, Zhiyong},
  booktitle = {Proceedings of the Twenty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-11}},
  publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
  editor    = {Toby Walsh},
  pages     = {1396--1400},
  year      = {2011},
  month     = {7},
  doi       = {10.5591/978-1-57735-516-8/IJCAI11-236},
  url       = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-236},
}

TY  - CPAPER
TI  - Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding
AU  - Ma, Xudong
AU  - Luo, Ping
AU  - Zhuang, Fuzhen
AU  - He, Qing
AU  - Shi, Zhongzhi
AU  - Shen, Zhiyong
T2  - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11
PB  - AAAI Press/International Joint Conferences on Artificial Intelligence
PY  - 2011
SP  - 1396
EP  - 1400
DO  - 10.5591/978-1-57735-516-8/IJCAI11-236
UR  - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-236
ER  -