Volume 27: Proceedings of ICML Workshop on Unsupervised and Transfer Learning, 02 July 2011, Bellevue, Washington, USA

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Editors: Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham Taylor, Daniel Silver

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Introduction

ICML2011 Unsupervised and Transfer Learning Workshop

David L. Silver, Isabelle Guyon, Graham Taylor, Gideon Dror, Vincent Lemaire ; PMLR 27:1-15

Fundamentals and theory

Deep Learning of Representations for Unsupervised and Transfer Learning

Yoshua Bengio ; PMLR 27:17-36

Autoencoders, Unsupervised Learning, and Deep Architectures

Pierre Baldi ; PMLR 27:37-49

Information Theoretic Model Selection for Pattern Analysis

Joachim M. Buhmann, Morteza H. Chehreghani, Mario Frank, Andreas P. Streich ; PMLR 27:51-64

Clustering: Science or Art?

Ulrike von Luxburg, Robert C. Williamson, Isabelle Guyon ; PMLR 27:65-79

Challenge contributions

Transfer Learning by Kernel Meta-Learning

Fabio Aiolli ; PMLR 27:81-95

Unsupervised and Transfer Learning Challenge: a Deep Learning Approach

Grégoire Mesnil Yann Dauphin, Xavier Glorot, Salah Rifai, Yoshua Bengio, Ian Goodfellow, Erick Lavoie, Xavier Muller, Guillaume Desjardins, David Warde-Farley, Pascal Vincent, Aaron Courville, James Bergstra ; PMLR 27:97-110

Stochastic Unsupervised Learning on Unlabeled Data

Chuanren Liu, Jianjun Xie, Yong Ge, Hui Xiong ; PMLR 27:111-122

Advances in transfer learning

Transfer Learning with Cluster Ensembles

Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya ; PMLR 27:123-132

Divide and Transfer: an Exploration of Segmented Transfer to Detect Wikipedia Vandalism

Si-Chi Chin, W. Nick Street ; PMLR 27:133-144

Self-measuring Similarity for Multi-task Gaussian Process

Kohei Hayashi, Takashi Takenouchi, Ryota Tomioka, Hisashi Kashima ; PMLR 27:145-153

Transfer Learning for Auto-gating of Flow Cytometry Data

Gyemin Lee, Lloyd Stoolman, Clayton Scott ; PMLR 27:155-165

Inductive Transfer for Bayesian Network Structure Learning

Alexandru Niculescu-Mizil, Rich Caruana ; PMLR 27:167-180

Unsupervised dimensionality reduction via gradient-based matrix factorization with two adaptive learning rates

Vladimir Nikulin, Tian-Hsiang Huang ; PMLR 27:181-194

One-Shot Learning with a Hierarchical Nonparametric Bayesian Model

Ruslan Salakhutdinov, Joshua Tenenbaum, Antonio Torralba ; PMLR 27:195-206

Multitask Learning in Computational Biology

Christian Widmer, Gunnar Rätsch ; PMLR 27:207-216

Transfer Learning in Sequential Decision Problems: A Hierarchical Bayesian Approach

Aaron Wilson, Alan Fern, Prasad Tadepalli ; PMLR 27:217-227

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