Using Both Latent and Supervised Shared Topics for Multitask Learning

Author:

Acharya Ayan,Rawal Aditya,Mooney Raymond J.,Hruschka Eduardo R.

Publisher

Springer Berlin Heidelberg

Reference43 articles.

1. Ando, R., Zhang, T.: A framework for learning predictive structures from multiple tasks and unlabeled data. Journal of Machine Learning Research 6, 1817–1853 (2005)

2. Ando, R.K.: Applying alternating structure optimization to word sense disambiguation. In: Proceedings of Computational Natural Language Learning (2006)

3. Argyriou, A., Micchelli, C.A., Pontil, M., Ying, Y.: A spectral regularization framework for multi-task structure learning. In: Proceedings of Neural Information Processing Systsems (2007)

4. Bakker, B., Heskes, T.: Task clustering and gating for Bayesian multitask learning. Journal of Machine Learning Research 4 (2003)

5. Lecture Notes in Artificial Intelligence;S. Ben-David,2003

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