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Honglak Lee
Honglak Lee
LG AI Research / U. Michigan
Подтвержден адрес электронной почты в домене umich.edu - Главная страница
Название
Процитировано
Процитировано
Год
An analysis of single-layer networks in unsupervised feature learning
A Coates, H Lee, AY Ng
AISTATS, 2011
48942011
Multimodal deep learning
J Ngiam, A Khosla, M Kim, J Nam, H Lee, AY Ng
Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011
42832011
Generative Adversarial Text to Image Synthesis
S Reed, Z Akata, X Yan, L Logeswaran, B Schiele, H Lee
arXiv preprint arXiv:1605.05396, 2016
42742016
Learning structured output representation using deep conditional generative models
K Sohn, H Lee, X Yan
Advances in Neural Information Processing Systems, 3483-3491, 2015
39492015
Efficient sparse coding algorithms
H Lee, A Battle, R Raina, AY Ng
Advances in neural information processing systems, 801-808, 2006
35512006
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
H Lee, R Grosse, R Ranganath, AY Ng
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
34982009
A simple unified framework for detecting out-of-distribution samples and adversarial attacks
K Lee, K Lee, H Lee, J Shin
Advances in Neural Information Processing Systems, 7167-7177, 2018
23122018
Self-taught learning: Transfer learning from unlabeled data
R Raina, A Battle, H Lee, B Packer, AY Ng
Proceedings of the 24th international conference on Machine learning, 759-766, 2007
22322007
Deep learning for detecting robotic grasps
I Lenz, H Lee, A Saxena
The International Journal of Robotics Research 34 (4-5), 705-724, 2015
20182015
Learning latent dynamics for planning from pixels
D Hafner, T Lillicrap, I Fischer, R Villegas, D Ha, H Lee, J Davidson
arXiv preprint arXiv:1811.04551, 2018
17212018
Unsupervised feature learning for audio classification using convolutional deep belief networks
H Lee, Y Largman, P Pham, AY Ng
Advances in neural information processing systems, 2009
15922009
Similarity of Neural Network Representations Revisited
S Kornblith, M Norouzi, H Lee, G Hinton
arXiv preprint arXiv:1905.00414, 2019
15392019
Sparse deep belief net model for visual area V2
H Lee, C Ekanadham, A Ng
Advances in neural information processing systems 20, 873-880, 2008
13702008
Evaluation of Output Embeddings for Fine-Grained Image Classification
Z Akata, S Reed, D Walter, H Lee, B Schiele
CVPR, 2015
12752015
Training Deep Neural Networks on Noisy Labels with Bootstrapping
S Reed, H Lee, D Anguelov, C Szegedy, D Erhan, A Rabinovich
arXiv preprint arXiv:1412.6596, 2014
12372014
Data-Efficient Hierarchical Reinforcement Learning
O Nachum, S Gu, H Lee, S Levine
arXiv preprint arXiv:1805.08296, 2018
10812018
Learning Deep Representations of Fine-Grained Visual Descriptions
S Reed, Z Akata, H Lee, B Schiele
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
10742016
Training confidence-calibrated classifiers for detecting out-of-distribution samples
K Lee, H Lee, K Lee, J Shin
arXiv preprint arXiv:1711.09325, 2017
10642017
Action-conditional video prediction using deep networks in atari games
J Oh, X Guo, H Lee, RL Lewis, S Singh
Advances in Neural Information Processing Systems, 2845-2853, 2015
10442015
Learning What and Where to Draw
S Reed, Z Akata, S Mohan, S Tenka, B Schiele, H Lee
NIPS, 2016
9392016
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