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ORCIDHonglak Lee
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- affiliation: University of Michigan, Ann Arbor, USA
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2020 – today
- 2023
[c139]Jinsu Yoo, Taehoon Kim, Sihaeng Lee, Seung Hwan Kim, Honglak Lee, Tae Hyun Kim:
Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution. WACV 2023: 4945-4954- [i119]Byoungjip Kim, Sungik Choi, Dasol Hwang, Moontae Lee, Honglak Lee:
Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching. CoRR abs/2301.02903 (2023) - [i118]Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee:
Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers. CoRR abs/2301.11578 (2023) - [i117]Wilka Carvalho, Angelos Filos, Richard L. Lewis, Honglak Lee, Satinder Singh:
Composing Task Knowledge with Modular Successor Feature Approximators. CoRR abs/2301.12305 (2023) - [i116]Yunseok Jang, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Moontae Lee, Honglak Lee:
Multimodal Subtask Graph Generation from Instructional Videos. CoRR abs/2302.08672 (2023) - [i115]Lajanugen Logeswaran, Sungryull Sohn, Yunseok Jang, Moontae Lee, Honglak Lee:
Unsupervised Task Graph Generation from Instructional Video Transcripts. CoRR abs/2302.09173 (2023) - [i114]Changyeon Kim, Jongjin Park, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
Preference Transformer: Modeling Human Preferences using Transformers for RL. CoRR abs/2303.00957 (2023) - [i113]Cheng Jiang, Xinhai Hou, Akhil Kondepudi, Asadur Chowdury, Christian W. Freudiger, Daniel A. Orringer, Honglak Lee, Todd C. Hollon:
Hierarchical discriminative learning improves visual representations of biomedical microscopy. CoRR abs/2303.01605 (2023) - [i112]Anthony Z. Liu, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee:
A Picture is Worth a Thousand Words: Language Models Plan from Pixels. CoRR abs/2303.09031 (2023) - 2022
- [c138]Yijie Guo, Qiucheng Wu, Honglak Lee:
Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Tasks. AAAI 2022: 6792-6800 - [c137]Anthony Z. Liu, Sungryull Sohn, Mahdi Qazwini, Honglak Lee:
Learning Parameterized Task Structure for Generalization to Unseen Entities. AAAI 2022: 7534-7541 - [c136]Yuan Li, Biaoyan Fang, Jiayuan He, Hiyori Yoshikawa, Saber A. Akhondi, Christian Druckenbrodt, Camilo Thorne, Zubair Afzal, Zenan Zhai, Kojiro Machi, Masaharu Yoshioka, Youngrok Jang, Hosung Song, Junho Lee, Gyeonghun Kim, Yireun Kim, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae, Darshini Mahendran, Christina Tang, Bridget T. McInnes, Timothy Baldwin, Karin Verspoor:
Extended Overview of ChEMU 2022 Evaluation Campaign: Information Extraction in Chemical Patents. CLEF (Working Notes) 2022: 758-781 - [c135]Youngrok Jang, Hosung Song, Junho Lee, Gyeonghun Kim, Yireun Kim, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae:
Context aware Named Entity Recognition and Relation Extraction with Domain-specific language model. CLEF (Working Notes) 2022: 782-796 - [c134]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. CVPR 2022: 16505-16515 - [c133]Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, Gunhee Kim:
Lipschitz-constrained Unsupervised Skill Discovery. ICLR 2022 - [c132]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. ICLR 2022 - [c131]Juhwan Noh, Dae-Woong Jeong, Kiyoung Kim, Sehui Han, Moontae Lee, Honglak Lee, Yousung Jung:
Path-Aware and Structure-Preserving Generation of Synthetically Accessible Molecules. ICML 2022: 16952-16968 - [c130]Sihaeng Lee, Eojindl Yi, Janghyeon Lee, Jinsu Yoo, Honglak Lee, Seung Hwan Kim:
Fully Convolutional Transformer with Local-Global Attention. IROS 2022: 552-559 - [c129]Lajanugen Logeswaran, Yao Fu, Moontae Lee, Honglak Lee:
Few-shot Subgoal Planning with Language Models. NAACL-HLT 2022: 5493-5506 - [c128]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. UAI 2022: 1857-1865 - [i111]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) - [i110]Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, Gunhee Kim:
Lipschitz-constrained Unsupervised Skill Discovery. CoRR abs/2202.00914 (2022) - [i109]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) - [i108]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) - [i107]Anthony Z. Liu, Sungryull Sohn, Mahdi Qazwini, Honglak Lee:
Learning Parameterized Task Structure for Generalization to Unseen Entities. CoRR abs/2203.15034 (2022) - [i106]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) - [i105]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) - [i104]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) - [i103]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) - [i102]Lajanugen Logeswaran, Yao Fu, Moontae Lee, Honglak Lee:
Few-shot Subgoal Planning with Language Models. CoRR abs/2205.14288 (2022) - [i101]Sungmin Cha, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon:
Is Continual Learning Truly Learning Representations Continually? CoRR abs/2206.08101 (2022) - [i100]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) - [i99]Jinwoo Kim, Tien Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong:
Pure Transformers are Powerful Graph Learners. CoRR abs/2207.02505 (2022) - [i98]Yijie Guo, Qiucheng Wu, Honglak Lee:
Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Tasks. CoRR abs/2207.09071 (2022) - [i97]Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee:
Grouping-matrix based Graph Pooling with Adaptive Number of Clusters. CoRR abs/2209.02939 (2022) - [i96]Janghyeon Lee, Jongsuk Kim, Hyounguk Shon, Bumsoo Kim, Seung Hwan Kim, Honglak Lee, Junmo Kim:
UniCLIP: Unified Framework for Contrastive Language-Image Pre-training. CoRR abs/2209.13430 (2022) - [i95]Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong:
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost. CoRR abs/2210.15541 (2022) - [i94]Jongseong Jang, Daeun Kyung, Seung Hwan Kim, Honglak Lee, Kyunghoon Bae, Edward Choi:
Significantly improving zero-shot X-ray pathology classification via fine-tuning pre-trained image-text encoders. CoRR abs/2212.07050 (2022) - [i93]Tiange Luo, Honglak Lee, Justin Johnson:
Neural Shape Compiler: A Unified Framework for Transforming between Text, Point Cloud, and Program. CoRR abs/2212.12952 (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 C. 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)