Google
Google Scholar
Semantic Scholar
MS Academic
CiteSeerX
ORCIDHonglak Lee
Person information
- affiliation: University of Michigan, Ann Arbor, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2020
[c102]Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh:
How Should an Agent Practice? AAAI 2020: 5454-5461- [c101]Haizhong Zheng, Ziqi Zhang, Juncheng Gu, Honglak Lee, Atul Prakash:
Efficient Adversarial Training With Transferable Adversarial Examples. CVPR 2020: 1178-1187 - [c100]Zizhao Zhang, Han Zhang, Sercan Ömer Arik, Honglak Lee, Tomas Pfister:
Distilling Effective Supervision From Severe Label Noise. CVPR 2020: 9291-9300 - [c99]Kimin Lee, Kibok Lee, Jinwoo Shin, Honglak Lee:
Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning. ICLR 2020 - [c98]Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Honglak Lee:
Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies. ICLR 2020 - [c97]Han Zhang, Zizhao Zhang, Augustus Odena, Honglak Lee:
Consistency Regularization for Generative Adversarial Networks. ICLR 2020 - [c96]Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed Chi, Craig Boutilier:
BRPO: Batch Residual Policy Optimization. IJCAI 2020: 2824-2830 - [c95]Shubham Dash, Giridharan Kumaravelu, Vijayakrishna Naganoor, Suraj Kiran Raman, Aditya Ramesh, Honglak Lee:
CompressNet: Generative Compression at Extremely Low Bitrates. WACV 2020: 2314-2322 - [i76]Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Honglak Lee:
Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies. CoRR abs/2001.00248 (2020) - [i75]Wonkwang Lee, Donggyun Kim, Seunghoon Hong, Honglak Lee:
High-Fidelity Synthesis with Disentangled Representation. CoRR abs/2001.04296 (2020) - [i74]Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena, Han Zhang:
Improved Consistency Regularization for GANs. CoRR abs/2002.04724 (2020) - [i73]Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed Chi, Craig Boutilier:
BRPO: Batch Residual Policy Optimization. CoRR abs/2002.05522 (2020) - [i72]Jared Quincy Davis, Krzysztof Choromanski, Jake Varley, Honglak Lee, Jean-Jacques E. Slotine, Valerii Likhosterov, Adrian Weller, Ameesh Makadia, Vikas Sindhwani:
Time Dependence in Non-Autonomous Neural ODEs. CoRR abs/2005.01906 (2020) - [i71]Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin:
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning. CoRR abs/2005.06800 (2020) - [i70]Suraj Kiran Raman, Aditya Ramesh, Vijayakrishna Naganoor, Shubham Dash, Giridharan Kumaravelu, Honglak Lee:
CompressNet: Generative Compression at Extremely Low Bitrates. CoRR abs/2006.08003 (2020) - [i69]Krzysztof Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani:
An Ode to an ODE. CoRR abs/2006.11421 (2020) - [i68]Haizhong Zheng, Ziqi Zhang, Honglak Lee, Atul Prakash:
Understanding and Diagnosing Vulnerability under Adversarial Attacks. CoRR abs/2007.08716 (2020) - [i67]Kuang-Huei Lee, Ian Fischer, Anthony Liu, Yijie Guo, Honglak Lee, John Canny, Sergio Guadarrama:
Predictive Information Accelerates Learning in RL. CoRR abs/2007.12401 (2020) - [i66]Tianhao Zhang, Hung-Yu Tseng, Lu Jiang, Honglak Lee, Irfan Essa, Weilong Yang:
Text as Neural Operator: Image Manipulation by Text Instruction. CoRR abs/2008.04556 (2020) - [i65]Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee:
i-Mix: A Strategy for Regularizing Contrastive Representation Learning. CoRR abs/2010.08887 (2020) - [i64]Guangxiang Zhu, Minghao Zhang, Honglak Lee, Chongjie Zhang:
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning. CoRR abs/2010.12142 (2020)
2010 – 2019
- 2019
- [c94]Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, Honglak Lee:
Zero-Shot Entity Linking by Reading Entity Descriptions. ACL (1) 2019: 3449-3460 - [c93]Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee:
Incremental Learning with Unlabeled Data in the Wild. CVPR Workshops 2019: 29-32 - [c92]Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee:
Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild. ICCV 2019: 312-321 - [c91]Yunseok Jang, Tianchen Zhao, Seunghoon Hong, Honglak Lee:
Adversarial Defense via Learning to Generate Diverse Attacks. ICCV 2019: 2740-2749 - [c90]Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee:
Contingency-Aware Exploration in Reinforcement Learning. ICLR (Poster) 2019 - [c89]Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine:
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. ICLR (Poster) 2019 - [c88]Dingdong Yang, Seunghoon Hong, Yunseok Jang, Tianchen Zhao, Honglak Lee:
Diversity-Sensitive Conditional Generative Adversarial Networks. ICLR (Poster) 2019 - [c87]Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson:
Learning Latent Dynamics for Planning from Pixels. ICML 2019: 2555-2565 - [c86]Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey E. Hinton:
Similarity of Neural Network Representations Revisited. ICML 2019: 3519-3529 - [c85]Kimin Lee, Sukmin Yun, Kibok Lee, Honglak Lee, Bo Li, Jinwoo Shin:
Robust Inference via Generative Classifiers for Handling Noisy Labels. ICML 2019: 3763-3772 - [c84]Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee:
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks. NeurIPS 2019: 81-91 - [c83]Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin P. Murphy, Honglak Lee:
Unsupervised learning of object structure and dynamics from videos. NeurIPS 2019: 92-102 - [p1]Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee:
Interpretable Text-to-Image Synthesis with Hierarchical Semantic Layout Generation. Explainable AI 2019: 77-95 - [i63]Dingdong Yang, Seunghoon Hong, Yunseok Jang, Tianchen Zhao, Honglak Lee:
Diversity-Sensitive Conditional Generative Adversarial Networks. CoRR abs/1901.09024 (2019) - [i62]Kimin Lee, Sukmin Yun, Kibok Lee, Honglak Lee, Bo Li, Jinwoo Shin:
Robust Inference via Generative Classifiers for Handling Noisy Labels. CoRR abs/1901.11300 (2019) - [i61]Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee:
Incremental Learning with Unlabeled Data in the Wild. CoRR abs/1903.12648 (2019) - [i60]Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey E. Hinton:
Similarity of Neural Network Representations Revisited. CoRR abs/1905.00414 (2019) - [i59]Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, Honglak Lee:
Zero-Shot Entity Linking by Reading Entity Descriptions. CoRR abs/1906.07348 (2019) - [i58]Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin Murphy, Honglak Lee:
Unsupervised Learning of Object Structure and Dynamics from Videos. CoRR abs/1906.07889 (2019) - [i57]Haonan Qiu, Chaowei Xiao, Lei Yang, Xinchen Yan, Honglak Lee, Bo Li:
SemanticAdv: Generating Adversarial Examples via Attribute-conditional Image Editing. CoRR abs/1906.07927 (2019) - [i56]Xinchen Yan, Mohi Khansari, Jasmine Hsu, Yuanzheng Gong, Yunfei Bai, Sören Pirk, Honglak Lee:
Data-Efficient Learning for Sim-to-Real Robotic Grasping using Deep Point Cloud Prediction Networks. CoRR abs/1906.08989 (2019) - [i55]Yijie Guo, Jongwook Choi, Marcin Moczulski, Samy Bengio, Mohammad Norouzi, Honglak Lee:
Efficient Exploration with Self-Imitation Learning via Trajectory-Conditioned Policy. CoRR abs/1907.10247 (2019) - [i54]Ofir Nachum, Haoran Tang, Xingyu Lu, Shixiang Gu, Honglak Lee, Sergey Levine:
Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning? CoRR abs/1909.10618 (2019) - [i53]Zizhao Zhang, Han Zhang, Sercan Ömer Arik, Honglak Lee, Tomas Pfister:
IEG: Robust Neural Network Training to Tackle Severe Label Noise. CoRR abs/1910.00701 (2019) - [i52]Kimin Lee, Kibok Lee, Jinwoo Shin, Honglak Lee:
A Simple Randomization Technique for Generalization in Deep Reinforcement Learning. CoRR abs/1910.05396 (2019) - [i51]Han Zhang, Zizhao Zhang, Augustus Odena, Honglak Lee:
Consistency Regularization for Generative Adversarial Networks. CoRR abs/1910.12027 (2019) - [i50]Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee:
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks. CoRR abs/1911.01655 (2019) - [i49]Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh:
How Should an Agent Practice? CoRR abs/1912.07045 (2019) - [i48]Haizhong Zheng, Ziqi Zhang, Juncheng Gu, Honglak Lee, Atul Prakash:
Efficient Adversarial Training with Transferable Adversarial Examples. CoRR abs/1912.11969 (2019) - 2018
- [c82]Lajanugen Logeswaran, Honglak Lee, Dragomir R. Radev:
Sentence Ordering and Coherence Modeling using Recurrent Neural Networks. AAAI 2018: 5285-5292 - [c81]Rui Zhang, Honglak Lee, Lazaros Polymenakos, Dragomir R. Radev:
Addressee and Response Selection in Multi-Party Conversations With Speaker Interaction RNNs. AAAI 2018: 5690-5697 - [c80]Kibok Lee, Kimin Lee, Kyle Min, Yuting Zhang, Jinwoo Shin, Honglak Lee:
Hierarchical Novelty Detection for Visual Object Recognition. CVPR 2018: 1034-1042 - [c79]Yuting Zhang, Yijie Guo, Yixin Jin, Yijun Luo, Zhiyuan He, Honglak Lee:
Unsupervised Discovery of Object Landmarks as Structural Representations. CVPR 2018: 2694-2703 - [c78]Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee:
Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis. CVPR 2018: 7986-7994 - [c77]Ruben Villegas, Jimei Yang, Duygu Ceylan, Honglak Lee:
Neural Kinematic Networks for Unsupervised Motion Retargetting. CVPR 2018: 8639-8648 - [c76]Xinchen Yan, Akash Rastogi, Ruben Villegas, Kalyan Sunkavalli, Eli Shechtman, Sunil Hadap, Ersin Yumer, Honglak Lee:
MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics. ECCV (5) 2018: 276-293 - [c75]Kimin Lee, Honglak Lee, Kibok Lee, Jinwoo Shin:
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples. ICLR (Poster) 2018 - [c74]Lajanugen Logeswaran, Honglak Lee:
An efficient framework for learning sentence representations. ICLR (Poster) 2018 - [c73]Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee:
Self-Imitation Learning. ICML 2018: 3875-3884 - [c72]Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee:
Hierarchical Long-term Video Prediction without Supervision. ICML 2018: 6033-6041 - [c71]Xinchen Yan, Jasmine Hsu, Mohammad Khansari, Yunfei Bai, Arkanath Pathak, Abhinav Gupta, James Davidson, Honglak Lee:
Learning 6-DOF Grasping Interaction via Deep Geometry-Aware 3D Representations. ICRA 2018: 1-9 - [c70]Seunghoon Hong, Xinchen Yan, Thomas E. Huang, Honglak Lee:
Learning Hierarchical Semantic Image Manipulation through Structured Representations. NeurIPS 2018: 2713-2723 - [c69]Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine:
Data-Efficient Hierarchical Reinforcement Learning. NeurIPS 2018: 3307-3317 - [c68]Lajanugen Logeswaran, Honglak Lee, Samy Bengio:
Content preserving text generation with attribute controls. NeurIPS 2018: 5108-5118 - [c67]Sungryull Sohn, Junhyuk Oh, Honglak Lee:
Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies. NeurIPS 2018: 7156-7166 - [c66]Kimin Lee, Kibok Lee, Honglak Lee, Jinwoo Shin:
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks. NeurIPS 2018: 7167-7177 - [c65]Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee:
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion. NeurIPS 2018: 8234-8244 - [i47]Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee:
Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis. CoRR abs/1801.05091 (2018) - [i46]Lajanugen Logeswaran, Honglak Lee:
An efficient framework for learning sentence representations. CoRR abs/1803.02893 (2018) - [i45]Kibok Lee, Kimin Lee, Kyle Min, Yuting Zhang, Jinwoo Shin, Honglak Lee:
Hierarchical Novelty Detection for Visual Object Recognition. CoRR abs/1804.00722 (2018) - [i44]Yuting Zhang, Yijie Guo, Yixin Jin, Yijun Luo, Zhiyuan He, Honglak Lee:
Unsupervised Discovery of Object Landmarks as Structural Representations. CoRR abs/1804.04412 (2018) - [i43]Ruben Villegas, Jimei Yang, Duygu Ceylan, Honglak Lee:
Neural Kinematic Networks for Unsupervised Motion Retargetting. CoRR abs/1804.05653 (2018) - [i42]Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine:
Data-Efficient Hierarchical Reinforcement Learning. CoRR abs/1805.08296 (2018) - [i41]Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee:
Hierarchical Long-term Video Prediction without Supervision. CoRR abs/1806.04768 (2018) - [i40]Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee:
Self-Imitation Learning. CoRR abs/1806.05635 (2018) - [i39]Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee:
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion. CoRR abs/1807.01675 (2018) - [i38]Kimin Lee, Kibok Lee, Honglak Lee, Jinwoo Shin:
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks. CoRR abs/1807.03888 (2018) - [i37]Sungryull Sohn, Junhyuk Oh, Honglak Lee:
Multitask Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies. CoRR abs/1807.07665 (2018) - [i36]Xinchen Yan, Akash Rastogi, Ruben Villegas, Kalyan Sunkavalli, Eli Shechtman, Sunil Hadap, Ersin Yumer, Honglak Lee:
MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics. CoRR abs/1808.04545 (2018) - [i35]Seunghoon Hong, Xinchen Yan, Thomas S. Huang, Honglak Lee:
Learning Hierarchical Semantic Image Manipulation through Structured Representations. CoRR abs/1808.07535 (2018) - [i34]Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine:
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. CoRR abs/1810.01257 (2018) - [i33]Lajanugen Logeswaran, Honglak Lee, Samy Bengio:
Content preserving text generation with attribute controls. CoRR abs/1811.01135 (2018) - [i32]Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee:
Contingency-Aware Exploration in Reinforcement Learning. CoRR abs/1811.01483 (2018) - [i31]Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson:
Learning Latent Dynamics for Planning from Pixels. CoRR abs/1811.04551 (2018) - [i30]Yijie Guo, Junhyuk Oh, Satinder Singh, Honglak Lee:
Generative Adversarial Self-Imitation Learning. CoRR abs/1812.00950 (2018) - 2017
- [c64]Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens:
Exploring the structure of a real-time, arbitrary neural artistic stylization network. BMVC 2017 - [c63]Yuting Zhang, Luyao Yuan, Yijie Guo, Zhiyuan He, I-An Huang, Honglak Lee:
Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries. CVPR 2017: 1090-1099 - [c62]Seunghoon Hong, Donghun Yeo, Suha Kwak, Honglak Lee, Bohyung Han:
Weakly Supervised Semantic Segmentation Using Web-Crawled Videos. CVPR 2017: 2224-2232 - [c61]Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, Honglak Lee:
Decomposing Motion and Content for Natural Video Sequence Prediction. ICLR (Poster) 2017 - [c60]Junhyuk Oh, Satinder P. Singh, Honglak Lee, Pushmeet Kohli:
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning. ICML 2017: 2661-2670 - [c59]Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, Honglak Lee:
Learning to Generate Long-term Future via Hierarchical Prediction. ICML 2017: 3560-3569 - [c58]Anna C. Gilbert, Yi Zhang, Kibok Lee, Yuting Zhang, Honglak Lee:
Towards Understanding the Invertibility of Convolutional Neural Networks. IJCAI 2017: 1703-1710 - [c57]Junhyuk Oh, Satinder Singh, Honglak Lee:
Value Prediction Network. NIPS 2017: 6118-6128 - [i29]Seunghoon Hong, Donghun Yeo, Suha Kwak, Honglak Lee, Bohyung Han:
Weakly Supervised Semantic Segmentation using Web-Crawled Videos. CoRR abs/1701.00352 (2017) - [i28]Yuting Zhang, Luyao Yuan, Yijie Guo, Zhiyuan He, I-An Huang, Honglak Lee:
Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries. CoRR abs/1704.03944 (2017) - [i27]Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, Honglak Lee:
Learning to Generate Long-term Future via Hierarchical Prediction. CoRR abs/1704.05831 (2017) - [i26]Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens:
Exploring the structure of a real-time, arbitrary neural artistic stylization network. CoRR abs/1705.06830 (2017) - [i25]Anna C. Gilbert, Yi Zhang, Kibok Lee, Yuting Zhang, Honglak Lee:
Towards Understanding the Invertibility of Convolutional Neural Networks. CoRR abs/1705.08664 (2017) - [i24]Junhyuk Oh, Satinder P. Singh, Honglak Lee, Pushmeet Kohli:
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning. CoRR abs/1706.05064 (2017) - [i23]Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, Honglak Lee:
Decomposing Motion and Content for Natural Video Sequence Prediction. CoRR abs/1706.08033 (2017) - [i22]Junhyuk Oh, Satinder Singh, Honglak Lee:
Value Prediction Network. CoRR abs/1707.03497 (2017) - [i21]Xinchen Yan, Mohi Khansari, Yunfei Bai, Jasmine Hsu, Arkanath Pathak, Abhinav Gupta, James Davidson, Honglak Lee:
Learning Grasping Interaction with Geometry-aware 3D Representations. CoRR abs/1708.07303 (2017) - [i20]Rui Zhang, Honglak Lee, Lazaros Polymenakos, Dragomir R. Radev:
Addressee and Response Selection in Multi-Party Conversations with Speaker Interaction RNNs. CoRR abs/1709.04005 (2017) - [i19]Kimin Lee, Honglak Lee, Kibok Lee, Jinwoo Shin:
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples. CoRR abs/1711.09325 (2017) - 2016
- [c56]Scott E. Reed, Zeynep Akata, Honglak Lee, Bernt Schiele:
Learning Deep Representations of Fine-Grained Visual Descriptions. CVPR 2016: 49-58 - [c55]Jimei Yang, Brian L. Price, Scott Cohen, Honglak Lee, Ming-Hsuan Yang:
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network. CVPR 2016: 193-202 - [c54]Seunghoon Hong, Junhyuk Oh, Honglak Lee, Bohyung Han:
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network. CVPR 2016: 3204-3212 - [c53]Xinchen Yan, Jimei Yang, Kihyuk Sohn, Honglak Lee:
Attribute2Image: Conditional Image Generation from Visual Attributes. ECCV (4) 2016: 776-791 - [c52]Yuting Zhang, Kibok Lee, Honglak Lee:
Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification. ICML 2016: 612-621 - [c51]Scott E. Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee:
Generative Adversarial Text to Image Synthesis. ICML 2016: 1060-1069 - [c50]Wenling Shang, Kihyuk Sohn, Diogo Almeida, Honglak Lee:
Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units. ICML 2016: 2217-2225 - [c49]Junhyuk Oh, Valliappa Chockalingam, Satinder P. Singh, Honglak Lee:
Control of Memory, Active Perception, and Action in Minecraft. ICML 2016: 2790-2799 - [c48]Xiaoxiao Guo, Satinder P. Singh, Richard L. Lewis, Honglak Lee:
Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games. IJCAI 2016: 1519-1525 - [c47]Rui Zhang, Honglak Lee, Dragomir R. Radev:
Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and Documents. HLT-NAACL 2016: 1512-1521 - [c46]Scott E. Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee:
Learning What and Where to Draw. NIPS 2016: 217-225 - [c45]Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, Honglak Lee:
Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision. NIPS 2016: 1696-1704 - [c44]Wenling Shang, Kihyuk Sohn, Honglak Lee, Anna C. Gilbert:
Discriminative Training of Structured Dictionaries via Block Orthogonal Matching Pursuit. SDM 2016: 243-251 - [i18]Jimei Yang, Scott E. Reed, Ming-Hsuan Yang, Honglak Lee:
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis. CoRR abs/1601.00706 (2016) - [i17]Jimei Yang, Brian L. Price, Scott Cohen, Honglak Lee, Ming-Hsuan Yang:
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network. CoRR abs/1603.04530 (2016) - [i16]Wenling Shang, Kihyuk Sohn, Diogo Almeida, Honglak Lee:
Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units. CoRR abs/1603.05201 (2016) - [i15]Xiaoxiao Guo, Satinder P. Singh, Richard L. Lewis, Honglak Lee:
Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games. CoRR abs/1604.07095 (2016) - [i14]Scott E. Reed, Zeynep Akata, Bernt Schiele, Honglak Lee:
Learning Deep Representations of Fine-grained Visual Descriptions. CoRR abs/1605.05395 (2016) - [i13]Scott E. Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee:
Generative Adversarial Text to Image Synthesis. CoRR abs/1605.05396 (2016) - [i12]Junhyuk Oh, Valliappa Chockalingam, Satinder P. Singh, Honglak Lee:
Control of Memory, Active Perception, and Action in Minecraft. CoRR abs/1605.09128 (2016) - [i11]