John Mern, Anil Yildiz, Zachary Sunberg and

Tapan Mukerji, Mykel J. Kochenderfer

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Anh Viet Do, Frank Neumann

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Shantanu Gupta, Zachary Lipton, David Childers

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reinforcement learning and planning, graph learning, causality

Lars Buesing, Nicolas Heess, Theophane Weber

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Tan Zhi-Xuan, Jordyn Mann, Tom Silver and

Josh Tenenbaum, Vikash Mansinghka

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

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Hendrik Baier, Michael Kaisers

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Planning and Scheduling, Markov Decisions Processes, Game Playing

Reda Ouhamma, Rémy Degenne, Vianney Perchet, Pierre Gaillard

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bandits, online learning

Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando and

Raffaele Perego, Salvatore Trani

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efficiency/effectiveness trade-offs, query-level earlyexit, additive regression trees, learning to rank

Alfonso Lobos Ruiz, Paul Grigas, Zheng Wen

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Deep Learning, Generative Models, Applications, Computer Vision; Applications, Visual Scene Analysis and Interpretation; Deep Learning, Adversarial Network, Algorithms, Online Learning Algorithms

Ayya Alieva, Aiden Aceves, Jialin Song and

Stephen Mayo, Yisong Yue, Yuxin Chen

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Anamay Chaturvedi, Jonathan Scarlett

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Abhimanyu Dubey, Alex `Sandy' Pentland

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Planning, Control, and Multiagent Learning

Giovanni Pellegrini, Alessandro Tibo, Paolo Frasconi and

Andrea Passerini, Manfred Jaeger

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Machine Learning, Deep Learning, Multi-instance; Multi-label; Multi-view learning, Relational Learning

Andrew Silva, Matthew Gombolay, Taylor Killian and

Ivan Jimenez, Sung-Hyun Son

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Linnan Wang, Rodrigo Fonseca, Yuandong Tian

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Keerti Anand, Rong Ge, Amit Kumar, Debmalya Panigrahi

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theory, optimization

Brenden Petersen, Mikel Landajuela Larma, Terrell N Mundhenk and

Claudio Santiago, Soo Kim, Joanne Kim

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reinforcement learning, automated machine learning, symbolic regression

Santiago Balseiro, Haihao Lu, Vahab Mirrokni

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Algorithms, Online Learning Algorithms

Alberto Maria Metelli, Matteo Papini, Pierluca D'Oro, Marcello Restelli

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Zhihao Jiang, Debmalya Panigrahi and Kevin Sun

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Online algorithms, paging

Sara Bernardini, Fabio Fagnani, Chiara Piacentini

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Greedy algorithms, Submodularity, Sequence functions, Search, Scheduling, Recommender Systems

Erik Lindgren, Sashank Reddi, Ruiqi Guo, Sanjiv Kumar

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deep learning, machine learning

Nawal Benabbou, Cassandre Leroy, Thibaut Lust, Patrice Perny

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Yiheng Lin, Guannan Qu, Longbo Huang, Adam Wierman

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reinforcement learning and planning, graph learning

Travis Dick, Wesley Pegden, Maria-Florina Balcan

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Insu Han, Jennifer Gillenwater

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Duanshun Li, Jing Liu, Dongeun Lee and

Ali S. Mazloom, Giridhar Kaushik , Kookjin Lee, Noseong Park

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Deep Learning

Yanchen Deng, Runsheng Yu, Xinrun Wang, Bo An

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Agent-based and Multi-agent Systems, Coordination and Cooperation, Constraint Optimization, Distributed Constraints

Keegan Harris, Hoda Heidari, Steven Wu

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optimization

Gaode Chen, Xinghua Zhang, Yanyan Zhao and

Cong Xue, Ji Xiang

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Data Mining, Recommender Systems, Big Data, Large-Scale Systems, Recommender Systems

Alvaro Velasquez, Brett Bissey, Lior Barak and

Andre Beckus, Ismail Alkhouri, Daniel Melcer, George Atia

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Panteha Naderian, Gabriel Loaiza-Ganem, Harry Braviner and

Anthony Caterini, Jesse C Cresswell, Tong Li, Animesh Garg

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reinforcement learning, goal reaching, Q-learning

Chaosheng Dong, Bo Zeng

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Learning Theory

Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl and

Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson

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Meta-Learning, Bayesian Reinforcement Learning, BAMDPs, Deep Reinforcement Learning

Wei Tang, Chien-Ju Ho, Yang Liu

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Laura Manduchi, Kieran Chin-Cheong, Holger Michel and

Sven Wellmann, Julia Vogt

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machine learning, robustness, generative model, clustering, representation learning

Johannes Fischer, Ömer Sahin Tas

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Online Learning, Active Learning, and Bandits

Guanya Shi, Yiheng Lin, Soon-Jo Chung and

Yisong Yue, Adam Wierman

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Mohammadreza Armandpour, Ali Sadeghian, Mingyuan Zhou

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machine learning