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ORCIDHonglak Lee
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- affiliation: University of Michigan, Ann Arbor, USA
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2020 – today
- 2022
[i104]Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust:
Environment Generation for Zero-Shot Compositional Reinforcement Learning. CoRR abs/2201.08896 (2022)- [i103]Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, Gunhee Kim:
Lipschitz-constrained Unsupervised Skill Discovery. CoRR abs/2202.00914 (2022) - [i102]Jinsu Yoo, Taehoon Kim, Sihaeng Lee, Seung Hwan Kim, Honglak Lee, Tae Hyun Kim:
Rich CNN-Transformer Feature Aggregation Networks for Super-Resolution. CoRR abs/2203.07682 (2022) - [i101]Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning. CoRR abs/2203.10050 (2022) - [i100]Anthony Z. Liu, Sungryull Sohn, Mahdi Qazwini, Honglak Lee:
Learning Parameterized Task Structure for Generalization to Unseen Entities. CoRR abs/2203.15034 (2022) - [i99]Jing Yu Koh, Harsh Agrawal, Dhruv Batra, Richard Tucker, Austin Waters, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson:
Simple and Effective Synthesis of Indoor 3D Scenes. CoRR abs/2204.02960 (2022) - [i98]Yunseok Jang, Ruben Villegas, Jimei Yang, Duygu Ceylan, Xin Sun, Honglak Lee:
RiCS: A 2D Self-Occlusion Map for Harmonizing Volumetric Objects. CoRR abs/2205.06975 (2022) - [i97]Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee:
Fast Inference and Transfer of Compositional Task Structures for Few-shot Task Generalization. CoRR abs/2205.12648 (2022) - [i96]Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
LEPUS: Prompt-based Unsupervised Multi-hop Reranking for Open-domain QA. CoRR abs/2205.12650 (2022) - [i95]Lajanugen Logeswaran, Yao Fu, Moontae Lee, Honglak Lee:
Few-shot Subgoal Planning with Language Models. CoRR abs/2205.14288 (2022) - [i94]Sungmin Cha, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon:
Is Continual Learning Truly Learning Representations Continually? CoRR abs/2206.08101 (2022) - [i93]Cheng Jiang, Asadur Chowdury, Xinhai Hou, Akhil Kondepudi, Christian W. Freudiger, Kyle Conway, Sandra Camelo-Piragua, Daniel A. Orringer, Honglak Lee, Todd C. Hollon:
OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology. CoRR abs/2206.08439 (2022) - 2021
- [c127]Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena, Han Zhang:
Improved Consistency Regularization for GANs. AAAI 2021: 11033-11041 - [c126]Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang:
Cross-Modal Contrastive Learning for Text-to-Image Generation. CVPR 2021: 833-842 - [c125]Jing Yu Koh, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson:
Pathdreamer: A World Model for Indoor Navigation. ICCV 2021: 14718-14728 - [c124]John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V. Le, Sergey Levine, Honglak Lee, Aleksandra Faust:
Evolving Reinforcement Learning Algorithms. ICLR 2021 - [c123]Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed H. Chi, Honglak Lee, Minmin Chen:
Batch Reinforcement Learning Through Continuation Method. ICLR 2021 - [c122]Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas E. Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong:
Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction. ICLR 2021 - [c121]Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee:
i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning. ICLR 2021 - [c120]Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu:
Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning. ICML 2021: 1953-1963 - [c119]Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
State Entropy Maximization with Random Encoders for Efficient Exploration. ICML 2021: 9443-9454 - [c118]Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee:
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks. ICML 2021: 9780-9790 - [c117]Yunke Wang, Chang Xu, Bo Du, Honglak Lee:
Learning to Weight Imperfect Demonstrations. ICML 2021: 10961-10970 - [c116]Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh:
Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment. IJCAI 2021: 2219-2226 - [c115]Tianhao Zhang, Hung-Yu Tseng, Lu Jiang, Weilong Yang, Honglak Lee, Irfan Essa:
Text as Neural Operator: Image Manipulation by Text Instruction. ACM Multimedia 2021: 1893-1902 - [c114]Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust:
Environment Generation for Zero-Shot Compositional Reinforcement Learning. NeurIPS 2021: 4157-4169 - [c113]Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin:
Improving Transferability of Representations via Augmentation-Aware Self-Supervision. NeurIPS 2021: 17710-17722 - [c112]Christopher Hoang, Sungryull Sohn, Jongwook Choi, Wilka Carvalho, Honglak Lee:
Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning. NeurIPS 2021: 26963-26975 - [c111]Simon Kornblith, Ting Chen, Honglak Lee, Mohammad Norouzi:
Why Do Better Loss Functions Lead to Less Transferable Features? NeurIPS 2021: 28648-28662 - [c110]Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang:
Text-to-Image Generation Grounded by Fine-Grained User Attention. WACV 2021: 237-246 - [i92]John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Sergey Levine, Quoc V. Le, Honglak Lee, Aleksandra Faust:
Evolving Reinforcement Learning Algorithms. CoRR abs/2101.03958 (2021) - [i91]Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang:
Cross-Modal Contrastive Learning for Text-to-Image Generation. CoRR abs/2101.04702 (2021) - [i90]Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
State Entropy Maximization with Random Encoders for Efficient Exploration. CoRR abs/2102.09430 (2021) - [i89]Izzeddin Gur, Natasha Jaques, Kevin Malta, Manoj Tiwari, Honglak Lee, Aleksandra Faust:
Adversarial Environment Generation for Learning to Navigate the Web. CoRR abs/2103.01991 (2021) - [i88]Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas E. Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong:
Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction. CoRR abs/2104.06697 (2021) - [i87]Jing Yu Koh, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson:
Pathdreamer: A World Model for Indoor Navigation. CoRR abs/2105.08756 (2021) - [i86]Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu:
Variational Empowerment as Representation Learning for Goal-Based Reinforcement Learning. CoRR abs/2106.01404 (2021) - [i85]Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee:
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks. CoRR abs/2107.06405 (2021) - [i84]Cheng Jiang, Abhishek Bhattacharya, Joseph Linzey, Rushikesh Joshi, Sung Jik Cha, Sudharsan Srinivasan, Daniel Alber, Akhil Kondepudi, Esteban Urias, Balaji Pandian, Wajd Al-Holou, Steve Sullivan, B. Gregory Thompson, Jason Heth, Chris Freudiger, Siri Khalsa, Donato Pacione, John G. Golfinos, Sandra Camelo-Piragua, Daniel A. Orringer, Honglak Lee, Todd Hollon
:
Contrastive Representation Learning for Rapid Intraoperative Diagnosis of Skull Base Tumors Imaged Using Stimulated Raman Histology. CoRR abs/2108.03555 (2021) - [i83]Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin:
Improving Transferability of Representations via Augmentation-Aware Self-Supervision. CoRR abs/2111.09613 (2021) - [i82]Christopher Hoang, Sungryull Sohn, Jongwook Choi, Wilka Carvalho, Honglak Lee:
Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning. CoRR abs/2111.09858 (2021) - [i81]Taehoon Kim, Gwangmo Song, Sihaeng Lee, Sangyun Kim, Yewon Seo, Soonyoung Lee, Seung Hwan Kim, Honglak Lee, Kyunghoon Bae:
L-Verse: Bidirectional Generation Between Image and Text. CoRR abs/2111.11133 (2021) - 2020
- [c109]Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh:
How Should an Agent Practice? AAAI 2020: 5454-5461 - [c108]Haizhong Zheng, Ziqi Zhang, Juncheng Gu, Honglak Lee, Atul Prakash:
Efficient Adversarial Training With Transferable Adversarial Examples. CVPR 2020: 1178-1187 - [c107]Zizhao Zhang, Han Zhang, Sercan Ömer Arik, Honglak Lee, Tomas Pfister:
Distilling Effective Supervision From Severe Label Noise. CVPR 2020: 9291-9300 - [c106]Haonan Qiu, Chaowei Xiao, Lei Yang, Xinchen Yan, Honglak Lee, Bo Li:
SemanticAdv: Generating Adversarial Examples via Attribute-Conditioned Image Editing. ECCV (14) 2020: 19-37 - [c105]Wonkwang Lee, Donggyun Kim, Seunghoon Hong, Honglak Lee:
High-Fidelity Synthesis with Disentangled Representation. ECCV (26) 2020: 157-174 - [c104]Kimin Lee, Kibok Lee, Jinwoo Shin, Honglak Lee:
Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning. ICLR 2020 - [c103]Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Honglak Lee:
Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies. ICLR 2020 - [c102]Han Zhang, Zizhao Zhang, Augustus Odena, Honglak Lee:
Consistency Regularization for Generative Adversarial Networks. ICLR 2020 - [c101]Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin:
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning. ICML 2020: 5757-5766 - [c100]Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier:
BRPO: Batch Residual Policy Optimization. IJCAI 2020: 2824-2830 - [c99]Krzysztof Marcin Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani:
Ode to an ODE. NeurIPS 2020 - [c98]Yijie Guo, Jongwook Choi, Marcin Moczulski, Shengyu Feng, Samy Bengio, Mohammad Norouzi, Honglak Lee:
Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards. NeurIPS 2020 - [c97]Kuang-Huei Lee, Ian Fischer, Anthony Z. Liu, Yijie Guo, Honglak Lee, John F. Canny, Sergio Guadarrama:
Predictive Information Accelerates Learning in RL. NeurIPS 2020 - [c96]Guangxiang Zhu, Minghao Zhang, Honglak Lee, Chongjie Zhang:
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning. NeurIPS 2020 - [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 - [i80]Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Honglak Lee:
Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies. CoRR abs/2001.00248 (2020) - [i79]Wonkwang Lee, Donggyun Kim, Seunghoon Hong, Honglak Lee:
High-Fidelity Synthesis with Disentangled Representation. CoRR abs/2001.04296 (2020) - [i78]Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena, Han Zhang:
Improved Consistency Regularization for GANs. CoRR abs/2002.04724 (2020) - [i77]Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier:
BRPO: Batch Residual Policy Optimization. CoRR abs/2002.05522 (2020) - [i76]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) - [i75]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) - [i74]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) - [i73]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) - [i72]Haizhong Zheng, Ziqi Zhang, Honglak Lee, Atul Prakash:
Understanding and Diagnosing Vulnerability under Adversarial Attacks. CoRR abs/2007.08716 (2020) - [i71]Kuang-Huei Lee, Ian Fischer, Anthony Z. Liu, Yijie Guo, Honglak Lee, John F. Canny, Sergio Guadarrama:
Predictive Information Accelerates Learning in RL. CoRR abs/2007.12401 (2020) - [i70]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) - [i69]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) - [i68]Guangxiang Zhu, Minghao Zhang, Honglak Lee, Chongjie Zhang:
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning. CoRR abs/2010.12142 (2020) - [i67]Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh:
Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in First-person Simulated 3D Environments. CoRR abs/2010.15195 (2020) - [i66]Simon Kornblith, Honglak Lee, Ting Chen, Mohammad Norouzi:
What's in a Loss Function for Image Classification? CoRR abs/2010.16402 (2020) - [i65]Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang:
Text-to-Image Generation Grounded by Fine-Grained User Attention. CoRR abs/2011.03775 (2020) - [i64]Lajanugen Logeswaran, Ann Lee, Myle Ott, Honglak Lee, Marc'Aurelio Ranzato, Arthur Szlam:
Few-shot Sequence Learning with Transformers. CoRR abs/2012.09543 (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,