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Author Information
Hugo Larochelle (Google Brain)
Finale Doshi-Velez (Harvard)
Marc Deisenroth (University College London)

Professor Marc Deisenroth is the DeepMind Chair in Artificial Intelligence at University College London and the Deputy Director of UCL's Centre for Artificial Intelligence. He also holds a visiting faculty position at the University of Johannesburg and Imperial College London. Marc's research interests center around data-efficient machine learning, probabilistic modeling and autonomous decision making. Marc was Program Chair of EWRL 2012, Workshops Chair of RSS 2013, EXPO-Co-Chair of ICML 2020, and Tutorials Co-Chair of NeurIPS 2021. In 2019, Marc co-organized the Machine Learning Summer School in London. He received Paper Awards at ICRA 2014, ICCAS 2016, and ICML 2020. He is co-author of the book [Mathematics for Machine Learning](https://mml-book.github.io) published by Cambridge University Press (2020).
Devi Parikh (Georgia Tech / Facebook AI Research (FAIR))
Julien Mairal (Inria)
Katja Hofmann (Microsoft Research)
Dr. Katja Hofmann is a Principal Researcher at the [Game Intelligence](http://aka.ms/gameintelligence/) group at [Microsoft Research Cambridge, UK](https://www.microsoft.com/en-us/research/lab/microsoft-research-cambridge/). There, she leads a research team that focuses on reinforcement learning with applications in modern video games. She and her team strongly believe that modern video games will drive a transformation of how we interact with AI technology. One of the projects developed by her team is [Project Malmo](https://www.microsoft.com/en-us/research/project/project-malmo/), which uses the popular game Minecraft as an experimentation platform for developing intelligent technology. Katja's long-term goal is to develop AI systems that learn to collaborate with people, to empower their users and help solve complex real-world problems. Before joining Microsoft Research, Katja completed her PhD in Computer Science as part of the [ILPS](https://ilps.science.uva.nl/) group at the [University of Amsterdam](https://www.uva.nl/en). She worked with Maarten de Rijke and Shimon Whiteson on interactive machine learning algorithms for search engines.
Phillip Isola (Massachusetts Institute of Technology)
Michael Bowling (University of Alberta / DeepMind)
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Finale Doshi-Velez -
2020 : Panel »
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Michael Bowling -
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2019 : Panel - The Role of Communication at Large: Aparna Lakshmiratan, Jason Yosinski, Been Kim, Surya Ganguli, Finale Doshi-Velez »
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2019 : Multi-Task Reinforcement Learning and Generalization »
Katja Hofmann -
2019 : Poster Presentations »
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2019 : Oral Presentations »
Janith Petangoda · Sergio Pascual-Diaz · Jordi Grau-Moya · Raphaël Marinier · Olivier Pietquin · Alexei Efros · Phillip Isola · Trevor Darrell · Christopher Lu · Deepak Pathak · Johan Ferret -
2019 : Invited Talk - Marc Deisenroth »
Marc Deisenroth -
2019 : The MineRL competition »
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2019 : Invited talk #4 »
Finale Doshi-Velez -
2019 : Finale Doshi-Velez: Combining Statistical methods with Human Input for Evaluation and Optimization in Batch Settings »
Finale Doshi-Velez -
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Alberto Bietti · Julien Mairal -
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2019 Tutorial: Reinforcement Learning: Past, Present, and Future Perspectives »
Katja Hofmann -
2018 : TBA 3 »
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2018 : How Players Speak to an Intelligent Game Character Using Natural Language Messages »
Katja Hofmann -
2018 : Finale Doshi-Velez »
Finale Doshi-Velez -
2018 : Panel on research process »
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2018 : Finale Doshi-Velez »
Finale Doshi-Velez -
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2018 Poster: Orthogonally Decoupled Variational Gaussian Processes »
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2017 : Finale Doshi-Velez »
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2017 : Automatic Model Selection in BNNs with Horseshoe Priors »
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2017 Workshop: Workshop on Meta-Learning »
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2017 : Panel Discussion »
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2017 : Towards Embodied Question Answering »
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2017 : Coffee break and Poster Session I »
Nishith Khandwala · Steve Gallant · Gregory Way · Aniruddh Raghu · Li Shen · Aydan Gasimova · Alican Bozkurt · William Boag · Daniel Lopez-Martinez · Ulrich Bodenhofer · Samaneh Nasiri GhoshehBolagh · Michelle Guo · Christoph Kurz · Kirubin Pillay · Kimis Perros · George H Chen · Alexandre Yahi · Madhumita Sushil · Sanjay Purushotham · Elena Tutubalina · Tejpal Virdi · Marc-Andre Schulz · Samuel Weisenthal · Bharat Srikishan · Petar Veličković · Kartik Ahuja · Andrew Miller · Erin Craig · Disi Ji · Filip Dabek · Chloé Pou-Prom · Hejia Zhang · Janani Kalyanam · Wei-Hung Weng · Harish Bhat · Hugh Chen · Simon Kohl · Mingwu Gao · Tingting Zhu · Ming-Zher Poh · Iñigo Urteaga · Antoine Honoré · Alessandro De Palma · Maruan Al-Shedivat · Pranav Rajpurkar · Matthew McDermott · Vincent Chen · Yanan Sui · Yun-Geun Lee · Li-Fang Cheng · Chen Fang · Sibt ul Hussain · Cesare Furlanello · Zeev Waks · Hiba Chougrad · Hedvig Kjellstrom · Finale Doshi-Velez · Wolfgang Fruehwirt · Yanqing Zhang · Lily Hu · Junfang Chen · Sunho Park · Gatis Mikelsons · Jumana Dakka · Stephanie Hyland · yann chevaleyre · Hyunwoo Lee · Xavier Giro-i-Nieto · David Kale · Michael Hughes · Gabriel Erion · Rishab Mehra · William Zame · Stojan Trajanovski · Prithwish Chakraborty · Kelly Peterson · Muktabh Mayank Srivastava · Amy Jin · Heliodoro Tejeda Lemus · Priyadip Ray · Tamas Madl · Joseph Futoma · Enhao Gong · Syed Rameel Ahmad · Eric Lei · Ferdinand Legros -
2017 : Contributed talk: Beyond Sparsity: Tree-based Regularization of Deep Models for Interpretability »
Mike Wu · Sonali Parbhoo · Finale Doshi-Velez -
2017 : Invited talk: The Role of Explanation in Holding AIs Accountable »
Finale Doshi-Velez -
2017 Workshop: Visually grounded interaction and language »
Florian Strub · Harm de Vries · Abhishek Das · Satwik Kottur · Stefan Lee · Mateusz Malinowski · Olivier Pietquin · Devi Parikh · Dhruv Batra · Aaron Courville · Jeremie Mary -
2017 : Panel: "How can we characterise the landscape of intelligent systems and locate human-like intelligence in it?" »
Josh Tenenbaum · Gary Marcus · Katja Hofmann -
2017 : Katja Hofmann: 'Video games and the road to collaborative AI' »
Katja Hofmann -
2017 Poster: Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure »
Alberto Bietti · Julien Mairal -
2017 Poster: Doubly Stochastic Variational Inference for Deep Gaussian Processes »
Hugh Salimbeni · Marc Deisenroth -
2017 Poster: Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes »
Taylor Killian · Samuel Daulton · Finale Doshi-Velez · George Konidaris -
2017 Spotlight: Doubly Stochastic Variational Inference for Deep Gaussian Processes »
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2017 Oral: Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes »
Taylor Killian · Samuel Daulton · Finale Doshi-Velez · George Konidaris -
2017 Spotlight: Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure »
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2017 Poster: Identification of Gaussian Process State Space Models »
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Alberto Bietti · Julien Mairal -
2017 Poster: A Meta-Learning Perspective on Cold-Start Recommendations for Items »
Manasi Vartak · Arvind Thiagarajan · Conrado Miranda · Jeshua Bratman · Hugo Larochelle -
2016 : BNNs for RL: A Success Story and Open Questions »
Finale Doshi-Velez -
2016 : Computer Curling: AI in Sports Analytics »
Michael Bowling -
2016 Poster: The Forget-me-not Process »
Kieran Milan · Joel Veness · James Kirkpatrick · Michael Bowling · Anna Koop · Demis Hassabis -
2016 Poster: End-to-End Kernel Learning with Supervised Convolutional Kernel Networks »
Julien Mairal -
2016 Demonstration: Project Malmo - Minecraft for AI Research »
Katja Hofmann · Matthew A Johnson · Fernando Diaz · Alekh Agarwal · Tim Hutton · David Bignell · Evelyne Viegas -
2016 Poster: Hierarchical Question-Image Co-Attention for Visual Question Answering »
Jiasen Lu · Jianwei Yang · Dhruv Batra · Devi Parikh -
2015 : Applications of Bayesian Optimization to Systems »
Marc Deisenroth -
2015 Workshop: Machine Learning From and For Adaptive User Technologies: From Active Learning & Experimentation to Optimization & Personalization »
Joseph Jay Williams · Yasin Abbasi Yadkori · Finale Doshi-Velez -
2015 : Data Driven Phenotyping for Diseases »
Finale Doshi-Velez -
2015 Poster: Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction »
Been Kim · Julie A Shah · Finale Doshi-Velez -
2015 Poster: A Universal Catalyst for First-Order Optimization »
Hongzhou Lin · Julien Mairal · Zaid Harchaoui -
2014 Workshop: Novel Trends and Applications in Reinforcement Learning »
Csaba Szepesvari · Marc Deisenroth · Sergey Levine · Pedro Ortega · Brian Ziebart · Emma Brunskill · Naftali Tishby · Gerhard Neumann · Daniel Lee · Sridhar Mahadevan · Pieter Abbeel · David Silver · Vicenç Gómez -
2014 Poster: Convolutional Kernel Networks »
Julien Mairal · Piotr Koniusz · Zaid Harchaoui · Cordelia Schmid -
2014 Spotlight: Convolutional Kernel Networks »
Julien Mairal · Piotr Koniusz · Zaid Harchaoui · Cordelia Schmid -
2014 Session: Oral Session 3 »
Hugo Larochelle -
2014 Poster: An Autoencoder Approach to Learning Bilingual Word Representations »
Sarath Chandar · Stanislas Lauly · Hugo Larochelle · Mitesh Khapra · Balaraman Ravindran · Vikas C Raykar · Amrita Saha -
2013 Workshop: Deep Learning »
Yoshua Bengio · Hugo Larochelle · Russ Salakhutdinov · Tomas Mikolov · Matthew D Zeiler · David Mcallester · Nando de Freitas · Josh Tenenbaum · Jian Zhou · Volodymyr Mnih -
2013 Workshop: Advances in Machine Learning for Sensorimotor Control »
Thomas Walsh · Alborz Geramifard · Marc Deisenroth · Jonathan How · Jan Peters -
2013 Session: Spotlight Session 10 »
Hugo Larochelle -
2013 Session: Spotlight Session 9 »
Hugo Larochelle -
2013 Poster: Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization »
Julien Mairal -
2013 Session: Spotlight Session 8 »
Hugo Larochelle -
2013 Session: Spotlight Session 7 »
Hugo Larochelle -
2013 Session: Spotlight Session 6 »
Hugo Larochelle -
2013 Session: Spotlight Session 5 »
Hugo Larochelle -
2013 Poster: RNADE: The real-valued neural autoregressive density-estimator »
Benigno Uria · Iain Murray · Hugo Larochelle -
2013 Session: Spotlight Session 4 »
Hugo Larochelle -
2013 Session: Spotlight Session 3 »
Hugo Larochelle -
2013 Session: Spotlight Session 2 »
Hugo Larochelle -
2013 Session: Spotlight Session 1 »
Hugo Larochelle -
2012 Poster: Sketch-Based Linear Value Function Approximation »
Marc Bellemare · Joel Veness · Michael Bowling -
2012 Poster: A Neural Autoregressive Topic Model »
Hugo Larochelle · Stanislas Lauly -
2012 Poster: Expectation Propagation in Gaussian Process Dynamical Systems »
Marc Deisenroth · Shakir Mohamed -
2012 Poster: Tractable Objectives for Robust Policy Optimization »
Katherine Chen · Michael Bowling -
2012 Poster: Practical Bayesian Optimization of Machine Learning Algorithms »
Jasper Snoek · Hugo Larochelle · Ryan Adams -
2011 Poster: Understanding the Intrinsic Memorability of Images »
Phillip Isola · Devi Parikh · Antonio Torralba · Aude Oliva -
2011 Poster: Variance Reduction in Monte-Carlo Tree Search »
Joel Veness · Marc Lanctot · Michael Bowling -
2010 Workshop: Learning and Planning from Batch Time Series Data »
Daniel Lizotte · Michael Bowling · Susan Murphy · Joelle Pineau · Sandeep Vijan -
2010 Oral: Learning to combine foveal glimpses with a third-order Boltzmann machine »
Hugo Larochelle · Geoffrey E Hinton -
2010 Poster: Learning to combine foveal glimpses with a third-order Boltzmann machine »
Hugo Larochelle · Geoffrey E Hinton -
2010 Poster: Network Flow Algorithms for Structured Sparsity »
Julien Mairal · Rodolphe Jenatton · Guillaume R Obozinski · Francis Bach -
2009 Workshop: Probabilistic Approaches for Control and Robotics »
Marc Deisenroth · Hilbert J Kappen · Emo Todorov · Duy Nguyen-Tuong · Carl Edward Rasmussen · Jan Peters -
2009 Poster: Strategy Grafting in Extensive Games »
Kevin G Waugh · Nolan Bard · Michael Bowling -
2009 Poster: Monte Carlo Sampling for Regret Minimization in Extensive Games »
Marc Lanctot · Kevin G Waugh · Martin A Zinkevich · Michael Bowling -
2008 Session: Oral session 3: Learning from Reinforcement: Modeling and Control »
Michael Bowling -
2008 Poster: SDL: Supervised Dictionary Learning »
Julien Mairal · Francis Bach · Jean A Ponce · Guillermo Sapiro · Andrew Zisserman -
2007 Spotlight: Stable Dual Dynamic Programming »
Tao Wang · Daniel Lizotte · Michael Bowling · Dale Schuurmans -
2007 Poster: Stable Dual Dynamic Programming »
Tao Wang · Daniel Lizotte · Michael Bowling · Dale Schuurmans -
2007 Spotlight: Regret Minimization in Games with Incomplete Information »
Martin A Zinkevich · Michael Johanson · Michael Bowling · Carmelo Piccione -
2007 Poster: Regret Minimization in Games with Incomplete Information »
Martin A Zinkevich · Michael Johanson · Michael Bowling · Carmelo Piccione -
2007 Poster: Computing Robust Counter-Strategies »
Michael Johanson · Martin A Zinkevich · Michael Bowling -
2006 Poster: Greedy Layer-Wise Training of Deep Networks »
Yoshua Bengio · Pascal Lamblin · Dan Popovici · Hugo Larochelle -
2006 Talk: Greedy Layer-Wise Training of Deep Networks »
Yoshua Bengio · Pascal Lamblin · Dan Popovici · Hugo Larochelle -
2006 Poster: iLSTD: Convergence, Eligibility Traces, and Mountain Car »
Alborz Geramifard · Michael Bowling · Martin A Zinkevich · Richard Sutton