Younggyo Seo, Kimin Lee, Ignasi Clavera Gilaberte and

Thanard Kurutach, Jinwoo Shin, Pieter Abbeel

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Markus Wulfmeier, Dushyant Rao, Roland Hafner and

Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala Bukkapatnam, Noah Siegel, Nicolas Heess, Martin Riedmiller

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Reinforcement Learning and Planning, Deep RL

Anurag Ajay, Aviral Kumar, Pulkit Agrawal and

Sergey Levine, Ofir Nachum

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Unsupervised Learning, Offline Reinforcement Learning, Primitive Discovery

Leonardo Lamanna, Alfonso Emilio Gerevini, Alessandro Saetti and

Luciano Serafini, Paolo Traverso

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Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar

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Reinforcement Learning - General

Arjun Manoharan, Rahul Ramesh, Balaraman Ravindran

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hierarchical reinforcement learning, policy distillation

Haiyong Jiang, Feilong Yan, Jianfei Cai and

Jianmin Zheng, Jun Xiao

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3d instance segmentation, stable matching, point cloud, label assignment

Kanika Madan, Nan Rosemary Ke, Anirudh Goyal and

Bernhard Schoelkopf, Yoshua Bengio

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better generalization, modular representations, learning mechanisms

Runze Wu, Hao Deng, Jianrong Tao and

Changjie Fan, Qi Liu, Liang Chen

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game scene preloading, periodicity, self-attention, behavior tracing, temporal irregularity

CAGLAR Gulcehre, Ziyu Wang, Alexander Novikov and

Thomas Paine, Sergio Gómez, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas

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Alejandro Suárez-Hernández, Javier Segovia-Aguas, Carme Torras, Guillem Alenyà

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David Nilsson, Aleksis Pirinen, Erik Gärtner, Cristian Sminchisescu

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Christopher Hoang, Sungryull Sohn, Jongwook Choi and

Wilka Carvalho, Honglak Lee

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reinforcement learning and planning, graph learning

Tonghan Wang, Heng Dong, Victor Lesser, Chongjie Zhang

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Planning, Control, and Multiagent Learning

Leonardo Lamanna, Alessandro Saetti, Luciano Serafini and

Alfonso Gerevini, Paolo Traverso

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Planning and Scheduling, Model-Based Reasoning, Planning Algorithms, Planning and Scheduling, Action, Change and Causality

Dimitrios Mallis, Enrique Sanchez, Matthew Bell, Georgios Tzimiropoulos

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Applications -> Privacy, Anonymity, and Security, Algorithms -> Adversarial Learning

Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Honglak Lee

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Meta reinforcement learning, subtask graph

Nakul Agarwal, Yi-Ting Chen, Behzad Dariush, Ming-Hsuan Yang

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Spatio-Temporal Action Localization, Unsupervised Domain Adaptation, Adversarial Learning, Video Analysis, Deep Learning

Siddharth Desai, Ishan Durugkar, Haresh Karnan and

Garrett Warnell, Josiah Hanna, Peter Stone

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Thanard Kurutach, Kara Liu, Aviv Tamar and

Pieter Abbeel, Christine Tung

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Planning, Control, and Multiagent Learning

Ron Dorfman, Idan Shenfeld, Aviv Tamar

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reinforcement learning and planning

Yadan Luo, Zijian Wang, Zi Huang, Mahsa Baktashmotlagh

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Applications - Computer Vision

Shijie Geng, Peng Gao, Moitreya Chatterjee and

Chiori Hori, Jonathan Le Roux, Yongfeng Zhang, Hongsheng Li, Anoop Cherian

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Qi Zheng, Chaoyue Wang, Dacheng Tao

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video and language, video captioning, action predicting

Mingde Zhao, Zhen Liu, Sitao Luan and

Shuyuan Zhang, Doina Precup, Yoshua Bengio

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deep learning, reinforcement learning and planning

Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou and

Amin Barekatain, Simon Schmitt, David Silver

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Reinforcement Learning and Planning, Deep RL

William Shen, Felipe Trevizan, Sylvie Thiébaux

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classical planning, learning heuristics, deep learning

Qitian Wu, Chenxiao Yang, Junchi Yan

Keywords Abstract Paper

deep learning, machine learning, graph learning, representation learning

Dilip Arumugam, Benjamin Van Roy

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theory, reinforcement learning and planning, bandits

Dilip Arumugam, Benjamin Van Roy

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Reinforcement Learning and Planning, Bandits

Mathieu Page Fortin, Brahim Chaib-draa

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Guoqiang Wei, Cuiling Lan, Wenjun Zeng and

Zhizheng Zhang, Zhibo Chen

Keywords Abstract Paper

machine learning, vision, domain adaptation

Manh-Ha Bui, Toan Tran, Anh Tran, Dinh Phung

Keywords Abstract Paper

meta learning, domain adaptation, representation learning

Wen Wang, Wei Zhang, Jun Rao and

Zhijie Qiu, Bo Zhang, Leyu Lin, Hongyuan Zha

Keywords Abstract Paper

user modeling, sequential group recommendation, graph representation learning

Teng Long, Pascal Mettes, Heng Tao Shen, Cees G. M. Snoek

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video retrieval, hyperbolic learning, hierarchical, zero-shot learning, action recognition, hyperbolic geometry

Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung and

Robinson Piramuthu, Yi-Hsuan Tsai, Ming-Hsuan Yang

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semantic segmentation, weakly-supervised learning, class activatin map, mixup augmentation, entropy regularization

Shaokai Ye, Kailu Wu, Mu Zhou and

Yunfei Yang, Sia Huat Tan, Kaidi Xu, Jiebo Song, Chenglong Bao, Kaisheng Ma

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domain adaptation, adversarial attack, adversarial learning, unsupervised learning, model compression, generative adversarial networks

A. Tuan Nguyen, Toan Tran, Yarin Gal, Atilim Gunes Baydin

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generative model, domain adaptation, representation learning

Xin Lin, Changxing Ding, Jinquan Zeng, Dacheng Tao

Keywords Abstract Paper

scene graph generation, message passing, visual genome dataset, visual relationship detection, open images dataset

Abubakar Siddique, Reza Jalil Mozhdehi, Henry Medeiros

Keywords Abstract Paper

Unsupervised learning, Subspace clustering, Heterogeneous autoencoder, Constraints k-means, Multi-task learning, Uncertainty learning, MOTS