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ORCIDUnsupervised and Transfer Learning - Workshop held at ICML 2011
- Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham W. Taylor, Daniel L. Silver:
Unsupervised and Transfer Learning - Workshop held at ICML 2011, Bellevue, Washington, USA, July 2, 2011. JMLR Proceedings 27, JMLR.org 2012
Introduction
- Daniel L. Silver, Isabelle Guyon, Graham W. Taylor, Gideon Dror, Vincent Lemaire:
ICML2011 Unsupervised and Transfer Learning Workshop. 1-16
Fundamentals and theory
- Yoshua Bengio:
Deep Learning of Representations for Unsupervised and Transfer Learning. 17-36 - Pierre Baldi:
Autoencoders, Unsupervised Learning, and Deep Architectures. 37-50 - Joachim M. Buhmann, Morteza Haghir Chehreghani, Mario Frank, Andreas P. Streich:
Information Theoretic Model Selection for Pattern Analysis. 51-64 - Ulrike von Luxburg, Robert C. Williamson, Isabelle Guyon:
Clustering: Science or Art? 65-80
Challenge contributions
- Fabio Aiolli:
Transfer Learning by Kernel Meta-Learning. 81-95 - Grégoire Mesnil, Yann N. Dauphin, Xavier Glorot
, Salah Rifai, Yoshua Bengio, Ian J. Goodfellow, Erick Lavoie, Xavier Muller, Guillaume Desjardins, David Warde-Farley, Pascal Vincent, Aaron C. Courville, James Bergstra:
Unsupervised and Transfer Learning Challenge: a Deep Learning Approach. 97-110 - Chuanren Liu, Jianjun Xie, Yong Ge, Hui Xiong:
Stochastic Unsupervised Learning on Unlabeled Data. 111-122
Advances in transfer learning
- Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya:
Transfer Learning with Cluster Ensembles. 123-132 - Si-Chi Chin, W. Nick Street:
Divide and Transfer: an Exploration of Segmented Transfer to Detect Wikipedia Vandalism. 133-144 - Kohei Hayashi, Takashi Takenouchi, Ryota Tomioka, Hisashi Kashima:
Self-measuring Similarity for Multi-task Gaussian Process. 145-154 - Gyemin Lee, Lloyd Stoolman, Clayton Scott:
Transfer Learning for Auto-gating of Flow Cytometry Data. 155-166 - Alexandru Niculescu-Mizil, Rich Caruana:
Inductive Transfer for Bayesian Network Structure Learning. 167-180 - Vladimir Nikulin, Tian-Hsiang Huang:
Unsupervised dimensionality reduction via gradient-based matrix factorization with two adaptive learning rates. 181-194 - Ruslan Salakhutdinov, Joshua B. Tenenbaum, Antonio Torralba:
One-Shot Learning with a Hierarchical Nonparametric Bayesian Model. 195-206 - Christian Widmer, Gunnar Rätsch:
Multitask Learning in Computational Biology. 207-216 - Aaron Wilson, Alan Fern, Prasad Tadepalli:
Transfer Learning in Sequential Decision Problems: A Hierarchical Bayesian Approach. 217-227
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