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All publications by Honglak Lee
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Action-Conditional Video Prediction using Deep Networks in Atari Games
Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis and Satinder Singh
Advances in Neural Information Processing Systems 28, 2015


Deep Visual Analogy-Making
Scott E. Reed, Yi Zhang, Yuting Zhang and Honglak Lee
Advances in Neural Information Processing Systems 28, 2015


Learning Structured Output Representation using Deep Conditional Generative Models
Kihyuk Sohn, Honglak Lee and Xinchen Yan
Advances in Neural Information Processing Systems 28, 2015


Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis
Jimei Yang, Scott E. Reed, Ming-hsuan Yang and Honglak Lee
Advances in Neural Information Processing Systems 28, 2015


Learning to Disentangle Factors of Variation with Manifold Interaction
Scott Reed, Kihyuk Sohn, Yuting Zhang and Honglak Lee
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Structured Recurrent Temporal Restricted Boltzmann Machines
Roni Mittelman, Benjamin Kuipers, Silvio Savarese and Honglak Lee
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning
Xiaoxiao Guo, Satinder Singh, Honglak Lee, Richard L. Lewis and Xiaoshi Wang
Advances in Neural Information Processing Systems 27, 2014


Improved Multimodal Deep Learning with Variation of Information
Kihyuk Sohn, Wenling Shang and Honglak Lee
Advances in Neural Information Processing Systems 27, 2014


Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines
Kihyuk Sohn, Guanyu Zhou, Chansoo Lee and Honglak Lee
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Robust Image Denoising with Multi-Column Deep Neural Networks
Forest Agostinelli, Michael R. Anderson and Honglak Lee
Advances in Neural Information Processing Systems 26, 2013


Learning to Align from Scratch
Gary Huang, Marwan Mattar, Honglak Lee and Erik G. Learned-miller
Advances in Neural Information Processing Systems 25, 2012


Learning Invariant Representations with Local Transformations
Kihyuk Sohn and Honglak Lee
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Online Incremental Feature Learning with Denoising Autoencoders
Guanyu Zhou, Kihyuk Sohn and Honglak Lee
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Efficient Distributed Linear Classification Algorithms via the Alternating Direction Method of Multipliers
Caoxie Zhang, Honglak Lee and Kang G. Shin
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Efficient and Exact MAP-MRF Inference using Branch and Bound
Min Sun, Murali Telaprolu, Honglak Lee and Silvio Savarese
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Multimodal Deep Learning
Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam, Honglak Lee and Andrew Y. Ng
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


An Analysis of Single-Layer Networks in Unsupervised Feature Learning
Adam Coates, Andrew Y. Ng and Honglak Lee
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
Honglak Lee, Roger Grosse, Rajesh Ranganath and Andrew Y. Ng
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Unsupervised feature learning for audio classification using convolutional deep belief networks
Honglak Lee, Peter Pham, Yan Largman and Andrew Y. Ng
Advances in Neural Information Processing Systems 22, 2009


Measuring Invariances in Deep Networks
Ian Goodfellow, Honglak Lee, Quoc V. Le, Andrew Saxe and Andrew Y. Ng
Advances in Neural Information Processing Systems 22, 2009


Self-taught learning: transfer learning from unlabeled data
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer and Andrew Y. Ng
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Sparse deep belief net model for visual area V2
Honglak Lee, Chaitanya Ekanadham and Andrew Y. Ng
Advances in Neural Information Processing Systems 20, 2007


Efficient sparse coding algorithms
Honglak Lee, Alexis Battle, Rajat Raina and Andrew Y. Ng
Advances in Neural Information Processing Systems 19, 2006