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Feature learning forms the cornerstone for tackling challenging learning problems in domains such as speech, computer vision and natural language processing.
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Estimation of non-normalized statistical models by score matching
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Analysis of representations for domain adaptation
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Domain adaptation with structural correspondence learning
John Blitzer, Ryan McDonald, and Fernando Pereira · 2006
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Correcting sample selection bias by unlabeled data
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Multi-conditional learning: Generative/discriminative training for clustering and classification
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Rajat Raina, Andrew Y Ng, and Daphne Koller · 2006
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Learning visual representations using images with captions
Ariadna Quattoni, Michael Collins, and Trevor Darrell · 2007
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Self-taught learning: transfer learning from unlabeled data
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer, and Andrew Y Ng · 2007
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Cross-domain video concept detection using adaptive svms
Jun Yang, Rong Yan, and Alexander G Hauptmann · 2007
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Flexible latent variable models for multi-task learning
Jian Zhang, Zoubin Ghahramani, and Yiming Yang · 2008
What regularized auto-encoders learn from the data generating distribution
Guillaume Alain and Yoshua Bengio · 2012
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Provable bounds for learning some deep representations
Sanjeev Arora, Aditya Bhaskara, Rong Ge, and Tengyu Ma · 2013
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Representation learning: A review and new perspectives
Yoshua Bengio, Aaron Courville, and Pascal Vincent · 2013
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Connecting the dots with landmarks: Discriminatively learning domain-invariant features for unsupervised domain adaptation
Boqing Gong, Kristen Grauman, and Fei Sha · 2013
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Efficient learning of domain-invariant image representations
Judy Hoffman, Erik Rodner, Jeff Donahue, Trevor Darrell, and Kate Saenko · 2013
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Zero-shot domain adaptation: A multi-view approach
John Blitzer, Dean P Foster, and Sham M Kakade · 2009
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Interpretation and generalization of score matching
Siwei Lyu · 2009
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Supervised dictionary learning
Julien Mairal, Jean Ponce, Guillermo Sapiro, Andrew Zisserman, and Francis R Bach · 2009
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Domain adaptation with multiple sources
Yishay Mansour, Mehryar Mohri, and Afshin Rostamizadeh · 2009
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A theory of learning from different domains
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Deep learning of representations for unsupervised and transfer learning
Yoshua Bengio · 2011
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Parametric stein operators and variance bounds
Christophe Ley and Yvik Swan · 2013
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Overfeat: Integrated recognition, localization and detection using convolutional networks
Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, and Yann LeCun · 2013
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Zero-shot learning through cross-modal transfer
Richard Socher, Milind Ganjoo, Christopher D Manning, and Andrew Ng · 2013
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Nonparametric estimation of multi-view latent variable models
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Robust and discriminative self-taught learning
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Visualizing and understanding convolutional neural networks
Matthew D Zeiler and Rob Fergus · 2013
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Learning Sparsely Used Overcomplete Dictionaries
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