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2020 – today
- 2024
[c83]David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause:
Learning Safety Constraints from Demonstrations with Unknown Rewards. AISTATS 2024: 2386-2394- [i56]Massimiliano Patacchiola, Aliaksandra Shysheya, Katja Hofmann, Richard E. Turner:
Transformer Neural Autoregressive Flows. CoRR abs/2401.01855 (2024) - [i55]Sugandha Sharma, Guy Davidson, Khimya Khetarpal, Anssi Kanervisto, Udit Arora, Katja Hofmann, Ida Momennejad:
Toward Human-AI Alignment in Large-Scale Multi-Player Games. CoRR abs/2402.03575 (2024) - 2023
- [c82]Mingfei Sun, Sam Devlin, Jacob Beck, Katja Hofmann, Shimon Whiteson:
Trust Region Bounds for Decentralized PPO Under Non-stationarity. AAMAS 2023: 5-13 - [c81]Stephanie Milani
, Arthur Juliani, Ida Momennejad, Raluca Georgescu, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann:
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games. CHI 2023: 572:1-572:18 - [c80]Massimiliano Patacchiola, Mingfei Sun, Katja Hofmann, Richard E. Turner:
Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy Imitation. CoLLAs 2023: 878-908 - [c79]Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin:
Imitating Human Behaviour with Diffusion Models. ICLR 2023 - [i54]Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin:
Imitating Human Behaviour with Diffusion Models. CoRR abs/2301.10677 (2023) - [i53]Mingfei Sun, Benjamin Ellis, Anuj Mahajan, Sam Devlin, Katja Hofmann, Shimon Whiteson:
Trust-Region-Free Policy Optimization for Stochastic Policies. CoRR abs/2302.07985 (2023) - [i52]Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Georgescu, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann:
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games. CoRR abs/2303.02160 (2023) - [i51]David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause:
Learning Safety Constraints from Demonstrations with Unknown Rewards. CoRR abs/2305.16147 (2023) - [i50]Massimiliano Patacchiola, Mingfei Sun, Katja Hofmann, Richard E. Turner:
Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy Imitation. CoRR abs/2306.13554 (2023) - 2022
- [c78]Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson:
Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency. AAAI 2022: 8378-8385 - [c77]Evelyn Zuniga, Stephanie Milani, Guy Leroy, Jaroslaw Rzepecki, Raluca Georgescu, Ida Momennejad, David Bignell, Mingfei Sun, Alison Shaw, Gavin Costello, Mikhail Jacob, Sam Devlin, Katja Hofmann:
How Humans Perceive Human-like Behavior in Video Game Navigation. CHI Extended Abstracts 2022: 391:1-391:11 - [c76]David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause:
Interactively Learning Preference Constraints in Linear Bandits. ICML 2022: 13505-13527 - [c75]Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin:
Uni[MASK]: Unified Inference in Sequential Decision Problems. NeurIPS 2022 - [c74]Massimiliano Patacchiola, John Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E. Turner:
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification. NeurIPS 2022 - [i49]Mingfei Sun, Vitaly Kurin, Guoqing Liu, Sam Devlin, Tao Qin, Katja Hofmann, Shimon Whiteson:
You May Not Need Ratio Clipping in PPO. CoRR abs/2202.00079 (2022) - [i48]Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson:
Monotonic Improvement Guarantees under Non-stationarity for Decentralized PPO. CoRR abs/2202.00082 (2022) - [i47]Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin:
Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers. CoRR abs/2204.13326 (2022) - [i46]Julia Kiseleva, Ziming Li, Mohammad Aliannejadi, Shrestha Mohanty, Maartje ter Hoeve, Mikhail Burtsev, Alexey Skrynnik, Artem Zholus, Aleksandr I. Panov, Kavya Srinet, Arthur Szlam, Yuxuan Sun, Marc-Alexandre Côté, Katja Hofmann, Ahmed Awadallah, Linar Abdrazakov, Igor Churin, Putra Manggala, Kata Naszádi, Michiel van der Meer, Taewoon Kim:
Interactive Grounded Language Understanding in a Collaborative Environment: IGLU 2021. CoRR abs/2205.02388 (2022) - [i45]David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause:
Interactively Learning Preference Constraints in Linear Bandits. CoRR abs/2206.05255 (2022) - [i44]Massimiliano Patacchiola, John Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E. Turner:
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification. CoRR abs/2206.09843 (2022) - [i43]Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin:
UniMASK: Unified Inference in Sequential Decision Problems. CoRR abs/2211.10869 (2022) - 2021
- [j13]Laetitia Teodorescu, Katja Hofmann, Pierre-Yves Oudeyer:
SpatialSim: Recognizing Spatial Configurations of Objects With Graph Neural Networks. Frontiers Artif. Intell. 4: 782081 (2021) - [j12]Luisa M. Zintgraf, Sebastian Schulze, Cong Lu, Leo Feng, Maximilian Igl, Kyriacos Shiarlis, Yarin Gal, Katja Hofmann, Shimon Whiteson:
VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning. J. Mach. Learn. Res. 22: 289:1-289:39 (2021) - [c73]Lida Theodorou, Daniela Massiceti, Luisa M. Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, Katja Hofmann:
Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. ASSETS 2021: 27:1-27:12 - [c72]Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah:
Evaluating the Robustness of Collaborative Agents. AAMAS 2021: 1560-1562 - [c71]Luisa M. Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann:
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning. AAMAS 2021: 1712-1714 - [c70]Daniela Massiceti, Luisa M. Zintgraf, John Bronskill, Lida Theodorou, Matthew Tobias Harris, Edward Cutrell, Cecily Morrison, Katja Hofmann, Simone Stumpf:
ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition. ICCV 2021: 10798-10808 - [c69]Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann:
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation. ICML 2021: 2644-2653 - [c68]Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer:
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL. ICML 2021: 9052-9063 - [c67]Luisa M. Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson:
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning. ICML 2021: 12991-13001 - [c66]Julia Kiseleva, Ziming Li, Mohammad Aliannejadi, Shrestha Mohanty, Maartje ter Hoeve, Mikhail Burtsev, Alexey Skrynnik, Artem Zholus, Aleksandr Panov, Kavya Srinet, Arthur Szlam, Yuxuan Sun, Katja Hofmann, Marc-Alexandre Côté, Ahmed Hassan Awadallah, Linar Abdrazakov, Igor Churin, Putra Manggala, Kata Naszádi, Michiel van der Meer, Taewoon Kim:
Interactive Grounded Language Understanding in a Collaborative Environment: IGLU 2021. NeurIPS (Competition and Demos) 2021: 146-161 - [c65]Tristan Karch, Laetitia Teodorescu, Katja Hofmann, Clément Moulin-Frier, Pierre-Yves Oudeyer:
Grounding Spatio-Temporal Language with Transformers. NeurIPS 2021: 5236-5249 - [c64]John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Sebastian Nowozin, Richard E. Turner:
Memory Efficient Meta-Learning with Large Images. NeurIPS 2021: 24327-24339 - [c63]Robert Tyler Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann:
Strategically efficient exploration in competitive multi-agent reinforcement learning. UAI 2021: 1587-1596 - [e2]Hugo Jair Escalante, Katja Hofmann:
NeurIPS 2020 Competition and Demonstration Track, 6-12 December 2020, Virtual Event / Vancouver, BC, Canada. Proceedings of Machine Learning Research 133, PMLR 2021 [contents] - [i42]Luisa M. Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann:
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning. CoRR abs/2101.03864 (2021) - [i41]Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah:
Evaluating the Robustness of Collaborative Agents. CoRR abs/2101.05507 (2021) - [i40]Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer:
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL. CoRR abs/2103.09815 (2021) - [i39]Daniela Massiceti, Luisa M. Zintgraf, John Bronskill, Lida Theodorou, Matthew Tobias Harris, Edward Cutrell, Cecily Morrison, Katja Hofmann, Simone Stumpf:
ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition. CoRR abs/2104.03841 (2021) - [i38]Grgur Kovac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer:
SocialAI 0.1: Towards a Benchmark to Stimulate Research on Socio-Cognitive Abilities in Deep Reinforcement Learning Agents. CoRR abs/2104.13207 (2021) - [i37]Rafal Muszynski, Katja Hofmann, Jun Wang:
Learning to Win, Lose and Cooperate through Reward Signal Evolution. CoRR abs/2105.08187 (2021) - [i36]Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann:
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation. CoRR abs/2105.09637 (2021) - [i35]Mingfei Sun, Anuj Mahajan, Katja Hofmann, Shimon Whiteson:
SoftDICE for Imitation Learning: Rethinking Off-policy Distribution Matching. CoRR abs/2106.03155 (2021) - [i34]Tristan Karch, Laetitia Teodorescu, Katja Hofmann, Clément Moulin-Frier, Pierre-Yves Oudeyer:
Grounding Spatio-Temporal Language with Transformers. CoRR abs/2106.08858 (2021) - [i33]Grgur Kovac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer:
SocialAI: Benchmarking Socio-Cognitive Abilities in Deep Reinforcement Learning Agents. CoRR abs/2107.00956 (2021) - [i32]John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Sebastian Nowozin, Richard E. Turner:
Memory Efficient Meta-Learning with Large Images. CoRR abs/2107.01105 (2021) - [i31]Robert Tyler Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann:
Strategically Efficient Exploration in Competitive Multi-agent Reinforcement Learning. CoRR abs/2107.14698 (2021) - [i30]Julia Kiseleva, Ziming Li, Mohammad Aliannejadi, Shrestha Mohanty, Maartje ter Hoeve, Mikhail Burtsev, Alexey Skrynnik, Artem Zholus, Aleksandr I. Panov, Kavya Srinet, Arthur Szlam, Yuxuan Sun, Katja Hofmann, Michel Galley, Ahmed Hassan Awadallah:
NeurIPS 2021 Competition IGLU: Interactive Grounded Language Understanding in a Collaborative Environment. CoRR abs/2110.06536 (2021) - [i29]Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson:
Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency. CoRR abs/2112.06054 (2021) - 2020
- [c62]Mikhail Jacob, Sam Devlin, Katja Hofmann:
"It's Unwieldy and It Takes a Lot of Time" - Challenges and Opportunities for Creating Agents in Commercial Games. AIIDE 2020: 88-94 - [c61]Steindór Sæmundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth:
Variational Integrator Networks for Physically Structured Embeddings. AISTATS 2020: 3078-3087 - [c60]Ian A. Kash, Michael Sullins, Katja Hofmann:
Combining No-regret and Q-learning. AAMAS 2020: 593-601 - [c59]Aristide C. Y. Tossou, Christos Dimitrakakis, Jaroslaw Rzepecki, Katja Hofmann:
A Novel Individually Rational Objective In Multi-Agent Multi-Armed Bandits: Algorithms and Regret Bounds. AAMAS 2020: 1395-1403 - [c58]Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann:
AMRL: Aggregated Memory For Reinforcement Learning. ICLR 2020 - [c57]Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard E. Turner:
Conservative Uncertainty Estimation By Fitting Prior Networks. ICLR 2020 - [c56]Luisa M. Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson:
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning. ICLR 2020 - [c55]Rémy Portelas, Cédric Colas, Lilian Weng, Katja Hofmann, Pierre-Yves Oudeyer:
Automatic Curriculum Learning For Deep RL: A Short Survey. IJCAI 2020: 4819-4825 - [c54]Hugo Jair Escalante, Katja Hofmann:
NeurIPS 2020 Competition and Demonstration Track: Revised selected papers. NeurIPS (Competition and Demos) 2020: 1-2 - [i28]Rémy Portelas, Cédric Colas, Lilian Weng, Katja Hofmann, Pierre-Yves Oudeyer:
Automatic Curriculum Learning For Deep RL: A Short Survey. CoRR abs/2003.04664 (2020) - [i27]Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer:
Trying AGAIN instead of Trying Longer: Prior Learning for Automatic Curriculum Learning. CoRR abs/2004.03168 (2020) - [i26]Laetitia Teodorescu, Katja Hofmann, Pierre-Yves Oudeyer:
Recognizing Spatial Configurations of Objects with Graph Neural Networks. CoRR abs/2004.04546 (2020) - [i25]Brandon Houghton, Stephanie Milani, Nicholay Topin, William H. Guss, Katja Hofmann, Diego Perez Liebana, Manuela Veloso, Ruslan Salakhutdinov:
Guaranteeing Reproducibility in Deep Learning Competitions. CoRR abs/2005.06041 (2020) - [i24]Rika Antonova, Maksim Maydanskiy, Danica Kragic, Sam Devlin, Katja Hofmann:
Analytic Manifold Learning: Unifying and Evaluating Representations for Continuous Control. CoRR abs/2006.08718 (2020) - [i23]Mikhail Jacob, Sam Devlin, Katja Hofmann:
"It's Unwieldy and It Takes a Lot of Time." Challenges and Opportunities for Creating Agents in Commercial Games. CoRR abs/2009.00541 (2020) - [i22]Luisa M. Zintgraf, Leo Feng, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson:
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning. CoRR abs/2010.01062 (2020) - [i21]Rémy Portelas, Clément Romac, Katja Hofmann, Pierre-Yves Oudeyer:
Meta Automatic Curriculum Learning. CoRR abs/2011.08463 (2020)
2010 – 2019
- 2019
- [c53]Katja Hofmann:
Minecraft as AI Playground and Laboratory. CHI PLAY 2019: 1 - [c52]Luke Harries, Sebastian Lee, Jaroslaw Rzepecki, Katja Hofmann, Sam Devlin:
MazeExplorer: A Customisable 3D Benchmark for Assessing Generalisation in Reinforcement Learning. CoG 2019: 1-4 - [c51]Dino Stephen Ratcliffe, Katja Hofmann, Sam Devlin:
Win or Learn Fast Proximal Policy Optimisation. CoG 2019: 1-4 - [c50]Rémy Portelas, Cédric Colas, Katja Hofmann, Pierre-Yves Oudeyer:
Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments. CoRL 2019: 835-853 - [c49]Luisa M. Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, Shimon Whiteson:
Fast Context Adaptation via Meta-Learning. ICML 2019: 7693-7702 - [c48]Kamil Ciosek, Quan Vuong, Robert Tyler Loftin, Katja Hofmann:
Better Exploration with Optimistic Actor Critic. NeurIPS 2019: 1785-1796 - [c47]David Janz, Jiri Hron, Przemyslaw Mazur, Katja Hofmann, José Miguel Hernández-Lobato, Sebastian Tschiatschek:
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning. NeurIPS 2019: 4509-4518 - [c46]Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann:
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck. NeurIPS 2019: 13956-13968 - [i20]Diego Pérez-Liébana, Katja Hofmann, Sharada Prasanna Mohanty, Noburu Kuno, André Kramer, Sam Devlin, Raluca D. Gaina, Daniel Ionita:
The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition. CoRR abs/1901.08129 (2019) - [i19]William H. Guss, Cayden R. Codel, Katja Hofmann, Brandon Houghton, Noburu Kuno, Stephanie Milani, Sharada P. Mohanty, Diego Perez Liebana, Ruslan Salakhutdinov, Nicholay Topin, Manuela Veloso, Phillip Wang:
The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors. CoRR abs/1904.10079 (2019) - [i18]Aristide C. Y. Tossou, Christos Dimitrakakis, Jaroslaw Rzepecki, Katja Hofmann:
Near-Optimal Online Egalitarian learning in General Sum Repeated Matrix Games. CoRR abs/1906.01609 (2019) - [i17]Ian A. Kash, Michael Sullins, Katja Hofmann:
Combining No-regret and Q-learning. CoRR abs/1910.03094 (2019) - [i16]Rémy Portelas, Cédric Colas, Katja Hofmann, Pierre-Yves Oudeyer:
Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments. CoRR abs/1910.07224 (2019) - [i15]Luisa M. Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson:
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning. CoRR abs/1910.08348 (2019) - [i14]Steindór Sæmundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth:
Variational Integrator Networks for Physically Meaningful Embeddings. CoRR abs/1910.09349 (2019) - [i13]Kamil Ciosek, Quan Vuong, Robert Tyler Loftin, Katja Hofmann:
Better Exploration with Optimistic Actor-Critic. CoRR abs/1910.12807 (2019) - [i12]Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann:
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck. CoRR abs/1910.12911 (2019) - 2018
- [j11]Fraser Allison, Ewa Luger, Katja Hofmann:
How Players Speak to an Intelligent Game Character Using Natural Language Messages. Trans. Digit. Games Res. Assoc. 4(2) (2018) - [c45]Yanan Sui, Masrour Zoghi, Katja Hofmann, Yisong Yue:
Advancements in Dueling Bandits. IJCAI 2018: 5502-5510 - [c44]Daniel Cohen, Bhaskar Mitra, Katja Hofmann, W. Bruce Croft:
Cross Domain Regularization for Neural Ranking Models using Adversarial Learning. SIGIR 2018: 1025-1028 - [c43]Steindór Sæmundsson, Katja Hofmann, Marc Peter Deisenroth:
Meta Reinforcement Learning with Latent Variable Gaussian Processes. UAI 2018: 642-652 - [i11]Steindór Sæmundsson, Katja Hofmann, Marc Peter Deisenroth:
Meta Reinforcement Learning with Latent Variable Gaussian Processes. CoRR abs/1803.07551 (2018) - [i10]Daniel Cohen, Bhaskar Mitra, Katja Hofmann, W. Bruce Croft:
Cross Domain Regularization for Neural Ranking Models Using Adversarial Learning. CoRR abs/1805.03403 (2018) - [i9]Sebastian Tschiatschek, Kai Arulkumaran, Jan Stühmer, Katja Hofmann:
Variational Inference for Data-Efficient Model Learning in POMDPs. CoRR abs/1805.09281 (2018) - [i8]Justas Dauparas, Ryota Tomioka, Katja Hofmann:
Depth and nonlinearity induce implicit exploration for RL. CoRR abs/1805.11711 (2018) - [i7]Luisa M. Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, Shimon Whiteson:
CAML: Fast Context Adaptation via Meta-Learning. CoRR abs/1810.03642 (2018) - [i6]David Janz, Jiri Hron, José Miguel Hernández-Lobato, Katja Hofmann, Sebastian Tschiatschek:
Successor Uncertainties: exploration and uncertainty in temporal difference learning. CoRR abs/1810.06530 (2018) - 2017
- [j10]José Hernández-Orallo, Marco Baroni, Jordi Bieger, Nader Chmait, David L. Dowe, Katja Hofmann, Fernando Martínez-Plumed, Claes Strannegård, Kristinn R. Thórisson:
A New AI Evaluation Cosmos: Ready to Play the Game? AI Mag. 38(3): 66-69 (2017) - [c42]Mathew Monfort, Matthew Johnson, Aude Oliva, Katja Hofmann:
Asynchronous Data Aggregation for Training End to End Visual Control Networks. AAMAS 2017: 530-537 - [c41]Fraser Allison, Ewa Luger, Katja Hofmann:
Spontaneous Interactions with a Virtually Embodied Intelligent Assistant in Minecraft. CHI Extended Abstracts 2017: 2337-2344 - [i5]Vitaly Kurin, Sebastian Nowozin, Katja Hofmann, Lucas Beyer, Bastian Leibe:
The Atari Grand Challenge Dataset. CoRR abs/1705.10998 (2017) - 2016
- [j9]Katja Hofmann, Lihong Li, Filip Radlinski:
Online Evaluation for Information Retrieval. Found. Trends Inf. Retr. 10(1): 1-117 (2016) - [c40]Weinan Zhang, Ulrich Paquet, Katja Hofmann:
Collective Noise Contrastive Estimation for Policy Transfer Learning. AAAI 2016: 1408-1414 - [c39]Matthew Johnson, Katja Hofmann, Tim Hutton, David Bignell:
The Malmo Platform for Artificial Intelligence Experimentation. IJCAI 2016: 4246-4247 - [c38]Konstantina Christakopoulou, Filip Radlinski, Katja Hofmann:
Towards Conversational Recommender Systems. KDD 2016: 815-824 - [i4]Philipp Geiger, Katja Hofmann, Bernhard Schölkopf:
Experimental and causal view on information integration in autonomous agents. CoRR abs/1606.04250 (2016) - [i3]Christoph Dann, Katja Hofmann, Sebastian Nowozin:
Memory Lens: How Much Memory Does an Agent Use? CoRR abs/1611.06928 (2016) - [i2]Felix Leibfried, Nate Kushman, Katja Hofmann:
A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games. CoRR abs/1611.07078 (2016) - 2015
- [c37]Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi:
Contextual Dueling Bandits. COLT 2015: 563-587 - [c36]Anne Schuth, Katja Hofmann, Filip Radlinski:
Predicting Search Satisfaction Metrics with Interleaved Comparisons. SIGIR 2015: 463-472 - [c35]Yiwei Chen, Katja Hofmann:
Online Learning to Rank: Absolute vs. Relative. WWW (Companion Volume) 2015: 19-20 - [i1]Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi:
Contextual Dueling Bandits. CoRR abs/1502.06362 (2015) - 2014
- [j8]Katja Hofmann, Shimon Whiteson, Anne Schuth, Maarten de Rijke:
"Learning to rank for information retrieval from user interactions" by K. Hofmann, S. Whiteson, A. Schuth, and M. de Rijke with Martin Vesely as coordinator. SIGWEB Newsl. 2014(Spring): 5:1-5:7 (2014) - [c34]Katja Hofmann, Bhaskar Mitra, Filip Radlinski, Milad Shokouhi:
An Eye-tracking Study of User Interactions with Query Auto Completion. CIKM 2014: 549-558 - [c33]Katja Hofmann, Anne Schuth, Alejandro Bellogín, Maarten de Rijke:
Effects of Position Bias on Click-Based Recommender Evaluation. ECIR 2014: 624-630 - [c32]Katja Hofmann:
Online Experimentation for Information Retrieval. RuSSIR 2014: 21-41 - [c31]Bhaskar Mitra, Milad Shokouhi, Filip Radlinski, Katja Hofmann:
On user interactions with query auto-completion. SIGIR 2014: 1055-1058 - [e1]Maarten de Rijke, Tom Kenter, Arjen P. de Vries, ChengXiang Zhai, Franciska de Jong, Kira Radinsky, Katja Hofmann:
Advances in Information Retrieval - 36th European Conference on IR Research, ECIR 2014, Amsterdam, The Netherlands, April 13-16, 2014. Proceedings. Lecture Notes in Computer Science 8416, Springer 2014, ISBN 978-3-319-06027-9 [contents] - 2013
- [j7]Katja Hofmann, Shimon Whiteson, Maarten de Rijke:
Balancing exploration and exploitation in listwise and pairwise online learning to rank for information retrieval. Inf. Retr. 16(1): 63-90 (2013) - [j6]Katja Hofmann:
Fast and reliable online learning to rank for information retrieval. SIGIR Forum 47(2): 140 (2013) - [j5]Katja Hofmann, Shimon Whiteson, Maarten de Rijke:
Fidelity, Soundness, and Efficiency of Interleaved Comparison Methods. ACM Trans. Inf. Syst. 31(4): 17:1-17:43 (2013) - [c30]Anne Schuth, Katja Hofmann, Shimon Whiteson, Maarten de Rijke:
Lerot: an online learning to rank framework. LivingLab@CIKM 2013: 23-26 - [c29]Aleksandr Chuklin, Anne Schuth, Katja Hofmann, Pavel Serdyukov, Maarten de Rijke:
Evaluating aggregated search using interleaving. CIKM 2013: 669-678 - [c28]Katja Hofmann, Anne Schuth, Shimon Whiteson, Maarten de Rijke:
Reusing Historical Interaction Data for Faster Online Learning to Rank for IR. DIR 2013: 30-31 - [c27]Filip Radlinski, Katja Hofmann:
Practical Online Retrieval Evaluation. ECIR 2013: 878-881 - [c26]Katja Hofmann, Anne Schuth, Shimon Whiteson, Maarten de Rijke:
Reusing historical interaction data for faster online learning to rank for IR. WSDM 2013: 183-192 - [p3]Piek Vossen, Isa Maks, Roxane Segers, Hennie van der Vliet, Marie-Francine Moens, Katja Hofmann, Erik Tjong Kim Sang, Maarten de Rijke:
Cornetto: A Combinatorial Lexical Semantic Database for Dutch. Essential Speech and Language Technology for Dutch 2013: 165-184 - 2012
- [c25]Katja Hofmann, Fritz Behr, Filip Radlinski:
On caption bias in interleaving experiments. CIKM 2012: 115-124 - [c24]Katja Hofmann, Shimon Whiteson, Maarten de Rijke:
Estimating interleaved comparison outcomes from historical click data. CIKM 2012: 1779-1783 - [c23]Peter Lubell-Doughtie, Katja Hofmann:
Learning to Rank from Relevance Feedback for e-Discovery. ECIR 2012: 535-539 - 2011
- [j4]Corrado Boscarino, Katja Hofmann, Valentin Jijkoun, Edgar Meij, Maarten de Rijke, Wouter Weerkamp:
DIR 2011: the eleventh Dutch-Belgian information retrieval workshop. SIGIR Forum 45(1): 42-44 (2011) - [c22]Katja Hofmann, Shimon Whiteson, Maarten de Rijke:
A probabilistic method for inferring preferences from clicks. CIKM 2011: 249-258 - [c21]Katja Hofmann, Shimon Whiteson, Maarten de Rijke:
Balancing Exploration and Exploitation in Learning to Rank Online. ECIR 2011: 251-263 - [c20]Katja Hofmann, Shimon Whiteson, Maarten de Rijke:
Adapting Rankers Online. IRFC 2011: 1-2 - [c19]Katja Hofmann:
Search engines that learn online. SIGIR 2011: 1313-1314 - [c18]Bouke Huurnink, Richard Berendsen, Katja Hofmann, Edgar Meij, Maarten de Rijke:
The University of Amsterdam at the TREC 2011 Session Track. TREC 2011 - [p2]Erik Tjong Kim Sang, Katja Hofmann, Maarten de Rijke:
Extraction of Hypernymy Information from Text∗. Interactive Multi-modal Question-Answering 2011: 223-245 - 2010
- [j3]Katja Hofmann, Krisztian Balog, Toine Bogers, Maarten de Rijke:
Contextual factors for finding similar experts. J. Assoc. Inf. Sci. Technol. 61(5): 994-1014 (2010) - [j2]Jana Besser, Martha A. Larson, Katja Hofmann:
Podcast search: user goals and retrieval technologies. Online Inf. Rev. 34(3): 395-419 (2010) - [c17]Bouke Huurnink, Katja Hofmann, Maarten de Rijke, Marc Bron:
Validating Query Simulators: An Experiment Using Commercial Searches and Purchases. CLEF 2010: 40-51 - [c16]Katja Hofmann, Bouke Huurnink, Marc Bron, Maarten de Rijke:
Comparing click-through data to purchase decisions for retrieval evaluation. SIGIR 2010: 761-762 - [c15]Marc Bron, Jiyin He, Katja Hofmann, Edgar Meij, Maarten de Rijke, Manos Tsagkias, Wouter Weerkamp:
The University of Amsterdam at TREC 2010: Session, Entity and Relevance Feedback. TREC 2010
2000 – 2009
- 2009
- [c14]Katja Hofmann, Manos Tsagkias, Edgar Meij, Maarten de Rijke:
The impact of document structure on keyphrase extraction. CIKM 2009: 1725-1728 - [c13]Katja Hofmann, Maarten de Rijke, Bouke Huurnink, Edgar Meij:
A Semantic Perspective on Query Log Analysis. CLEF (Working Notes) 2009 - [c12]Erik F. Tjong Kim Sang, Katja Hofmann:
Lexical Patterns or Dependency Patterns: Which Is Better for Hypernym Extraction? CoNLL 2009: 174-182 - [c11]Valentin Jijkoun, Katja Hofmann:
Generating a Non-English Subjectivity Lexicon: Relations That Matter. EACL 2009: 398-405 - [c10]Jiyin He, Krisztian Balog, Katja Hofmann, Edgar Meij, Maarten de Rijke, Manos Tsagkias, Wouter Weerkamp:
Heuristic Ranking and Diversification of Web Documents. TREC 2009 - 2008
- [c9]Jana Besser, Katja Hofmann, Martha A. Larson:
An Exploratory Study of User Goals and Strategies in Podcast Search. LWA 2008: 27-34 - [c8]Bouke Huurnink, Katja Hofmann, Maarten de Rijke:
Assessing concept selection for video retrieval. Multimedia Information Retrieval 2008: 459-466 - [p1]Hilary J. Holz, Katja Hofmann, Catherine Reed:
Unobtrusive User Modeling For Adaptive Hypermedia. Personalization Techniques and Recommender Systems 2008: 61-84 - 2007
- [j1]Hilary J. Holz, Katja Hofmann, Catherine Reed:
Unobtrusive User Modeling for Adaptive Hypermedia. Int. J. Pattern Recognit. Artif. Intell. 21(2): 225-244 (2007) - [c7]Jabari O. Pulliam, Robert Sajan, Katja Hofmann:
Modeling Engagement in Educational Adaptive Hypermedia. AIED 2007: 695-696 - [c6]Valentin Jijkoun, Katja Hofmann, David Ahn, Mahboob Alam Khalid, Joris van Rantwijk, Maarten de Rijke, Erik F. Tjong Kim Sang:
The University of Amsterdam's Question Answering System at QA@CLEF 2007. CLEF 2007: 344-351 - [c5]Valentin Jijkoun, Katja Hofmann, David Ahn, Mahboob Alam Khalid, Joris van Rantwijk, Maarten de Rijke, Erik F. Tjong Kim Sang:
The University of Amsterdam at CLEF@QA 2007. CLEF (Working Notes) 2007 - [c4]Katja Hofmann, Erik F. Tjong Kim Sang:
Automatic extension of non-english wordnets. SIGIR 2007: 833-834 - [c3]Krisztian Balog, Katja Hofmann, Wouter Weerkamp, Maarten de Rijke:
Query and Document Models for Enterprise Search. TREC 2007 - [c2]Katja Hofmann, Valentin Jijkoun, Mahboob Alam Khalid, Joris van Rantwijk, Erik F. Tjong Kim Sang:
The University of Amsterdam at the TREC 2007 QA Track. TREC 2007 - 2005
- [c1]Katja Hofmann:
Subsymbolic User Modeling in Adaptive Hypermedia. AIED 2005: 962
Coauthor Index
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