Algorithmic Learning Theory: 22nd International Conference, by Jyrki Kivinen, Csaba Szepesvári, Esko Ukkonen, Thomas

By Jyrki Kivinen, Csaba Szepesvári, Esko Ukkonen, Thomas Zeugmann (auth.), Jyrki Kivinen, Csaba Szepesvári, Esko Ukkonen, Thomas Zeugmann (eds.)

This e-book constitutes the refereed lawsuits of the twenty second foreign convention on Algorithmic studying thought, ALT 2011, held in Espoo, Finland, in October 2011, co-located with the 14th overseas convention on Discovery technological know-how, DS 2011.
The 28 revised complete papers offered including the abstracts of five invited talks have been rigorously reviewed and chosen from a variety of submissions. The papers are divided into topical sections of papers on inductive inference, regression, bandit difficulties, on-line studying, kernel and margin-based equipment, clever brokers and different studying models.

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Extra info for Algorithmic Learning Theory: 22nd International Conference, ALT 2011, Espoo, Finland, October 5-7, 2011. Proceedings

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Advances in Neural Information Processing Systems (NIPS 2006), vol. 19, pp. 1137–1144. : Sparse feature learning for deep belief networks. , Roweis, S. ) Advances in Neural Information Processing Systems (NIPS 2007), vol. 20, pp. 1185–1192. : Contractive auto-encoders: Explicit invariance during feature extraction. : Learning representations by backpropagating errors. : Semantic hashing. In: Proceedings of the 2007 Workshop on Information Retrieval and Applications of Graphical Models (SIGIR 2007).

Auto-association by multilayer perceptrons and singular value decomposition. : Poly-logarithmic independence fools bounded-depth boolean circuits. : Quickly generating representative samples from an rbm-derived process. : Signature verification using a siamese time delay neural network. In: Advances in Pattern Recognition Systems using Neural Network Technologies, pp. 669–687. : Learning many related tasks at the same time with backpropagation. , Leen, T. ) Advances in Neural Information Processing Systems (NIPS 1994), vol.

Advances in Neural Information Processing Systems (NIPS 2007), vol. 20, pp. 1185–1192. : Contractive auto-encoders: Explicit invariance during feature extraction. : Learning representations by backpropagating errors. : Semantic hashing. In: Proceedings of the 2007 Workshop on Information Retrieval and Applications of Graphical Models (SIGIR 2007). : Deep Boltzmann machines. In: Proceedings of The Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS 2009), vol. 5, pp.

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