Yishay Mansour, Mehryar Mohri, Jae Ro and

Ananda Theertha Suresh, Ke Wu

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Yi Ren, Shangmin Guo, Matthieu Labeau and

Shay B. Cohen, Simon Kirby

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Compositionality, Multi-agent, Emergent language, Iterated learning

Kibok Lee, Yian Zhu, Kihyuk Sohn and

Chun-Liang Li, Jinwoo Shin, Honglak Lee

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self-supervised learning, unsupervised representation learning, data augmentation, MixUp, contrastive representation learning

Yukuo Cen, Jianwei Zhang, Xu Zou and

Chang Zhou, Hongxia Yang, Jie Tang

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recommender system, multi-interest framework, sequential recommendation

Marin Vlastelica Pogančić, Anselm Paulus, Vit Musil and

Georg Martius, Michal Rolinek

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combinatorial algorithms, deep learning, representation learning, optimization

Ruihui Li, Xianzhi Li, Pheng-Ann Heng, Chi-Wing Fu

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auto-augmentation framework, point cloud processing, sample-aware, jointly optimizing, classification

Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner and

Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Thomas Adler, David Kreil, Michael K Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter

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Attention, Associative Memory, Hopfield layer, Storage Capacity, Convergence, Energy, Modern Hopfield Network

Belinda Z. Li, Gabriel Stanovsky, Luke Zettlemoyer

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Coreference Resolution, active resolution, Active Learning, Discrete Annotation

Ruiying Geng, Binhua Li, Yongbin Li and

Jian Sun, Xiaodan Zhu

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Few-Shot Classification, few-short classification, Dynamic Networks, Dynamic DMIN

Corinna Cortes, Giulia DeSalvo, Claudio Gentile and

Mehryar Mohri, Ningshan Zhang

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Online Learning, Active Learning, and Bandits

Siyu Ren, Kenny Q. Zhu

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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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Ruoxi Sun, Hanjun Dai, Li Li and

Steven Kearnes, Bo Dai

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deep learning, machine learning, graph learning

Aviv Gabbay, Yedid Hoshen

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disentanglement, latent optimization, domain translation

Zhongwen Xu, Hado van Hasselt, Matteo Hessel and

Junhyuk Oh, Satinder Singh, David Silver

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Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont, Julien Mairal

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attention, bioinformatics, transformers, optimal transport, kernel methods

Kevin Ellis, Catherine Wong, Maxwell Nye and

Mathias Sablé-Meyer, Lucas Morales, Luke Hewitt, Luc Cary, Armando Solar-Lezama, Joshua B. Tenenbaum

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synthesis, neural, learning, refactoring

Idan Achituve, Haggai Maron, Gal Chechik

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Keren Fu, Deng-Ping Fan, Ge-Peng Ji, Qijun Zhao

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visual saliency, salient object detection, rgb-d, depth information, joint learning, dense connections, multi-modal features, feature fusion, deep learning, encoder-decoder

Hao Fei, Meishan Zhang, Bobo Li, Donghong Ji

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Xiaodong Liu, Yu Wang, Jianshu Ji and

Hao Cheng, Xueyun Zhu, Emmanuel Awa, Pengcheng He, Weizhu Chen, Hoifung Poon, Guihong Cao, Jianfeng Gao

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Natural Understanding, NLU tasks, classification, regression

Zhengbao Jiang, Wei Xu, Jun Araki, Graham Neubig

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Natural Analysis, Natural processing, dependency parsing, semantic labeling

Kai Sun, Richong Zhang, Samuel Mensah and

Yongyi Mao, Xudong Liu

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Zhonghua Wu, Qingyi Tao, Guosheng Lin, Jianfei Cai

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weakly supervised detection, webly supervised detection, object detection, domain adaptation, class activation mapping

Yuchen Lu, Yikang Shen, Siyuan Zhou and

Aaron Courville, Joshua B Tenenbaum, Chuang Gan

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Task Segmentation, Network Inductive Bias, Hierarchical Imitation Learning

Kwangho Kim, Jisu Kim, Manzil Zaheer and

Joon Kim, Frederic Chazal, Larry Wasserman

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Tianle Cai, Ruiqi Gao, Jason Lee, Qi Lei

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Theory, Statistical Learning Theory

Bowen Zhang, Hexiang Hu, Vihan Jain and

Eugene Ie, Fei Sha

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cross-modal retrieval, referring expression, compositional recognition, pre-training

Nick Pawlowski, Daniel Coelho de Castro, Ben Glocker

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Changsheng Li, Chen Yang, Bo Liu and

Ye Yuan, Guoren Wang

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Jayneel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc

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deep learning, interpretability

Zilu Guo, Zhongqiang Huang, Kenny Q. Zhu and

Guandan Chen, Kaibo Zhang, Boxing Chen, Fei Huang

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Natural Language Processing, Machine Translation, Natural Language Generation, NLP Applications and Tools

Shunya Minami, Song Liu, Stephen Wu and

Kenji Fukumizu, Ryo Yoshida

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Mark Rowland, Will Dabney, Remi Munos

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Ruixiang ZHANG, Katsuhiko Ishiguro, Masanori Koyama

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Learning Theory

Dan Kushnir, Benjamin Mirabelli

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Maryam Majzoubi, Chicheng Zhang, Rajan Chari and

Akshay Krishnamurthy, John Langford, Alex Slivkins Slivkins

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Tatyana Ruzsics, Olga Sozinova, Ximena Gutierrez-Vasques, Tanja Samardzic

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Han Peng, Ge Li, Wenhan Wang and

YunFei Zhao, Zhi Jin

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machine learning, transformers

Xiantong Zhen, Yingjun Du, Huan Xiong and

Qiang Qiu, Cees Snoek, Ling Shao

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