Sebastian Tschiatschek

108 papers A* 23A 12B 2Misc 1Journal 51Unranked 18

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Breaking the Reclustering Barrier in Centroid-based Deep Clustering. ICLR Lukas Miklautz, Timo Klein, Kevin Sidak, Collin Leiber, Thomas Lang, Andrii Shkabrii, Sebastian Tschiatschek, Claudia Plant
2025	J	`jnl`	Expressiveness of Parametrized Distributions over DAGs for Causal Discovery. Trans. Mach. Learn. Res. Simon Rittel, Sebastian Tschiatschek
2025	J	`jnl`	Information that matters: Exploring information needs of people affected by algorithmic decisions. Int. J. Hum. Comput. Stud. Timothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek
2025	A	`conf`	On Constant Regret for Low-Rank MDPs. UAI Alexander Sturm, Sebastian Tschiatschek
2025	J	`jnl`	Prompt Optimization Across Multiple Agents for Representing Diverse Human Populations. CoRR Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla
2025	A*	`conf`	Rule-Guided Reinforcement Learning Policy Evaluation and Improvement. IJCAI Martin Tappler, Ignacio D. Lopez-Miguel, Sebastian Tschiatschek, Ezio Bartocci
2025	J	`jnl`	Rule-Guided Reinforcement Learning Policy Evaluation and Improvement. CoRR Martin Tappler, Ignacio D. Lopez-Miguel, Sebastian Tschiatschek, Ezio Bartocci
2025	—	`conf`	Synthesizing High-Quality Programming Tasks with LLM-Based Expert and Student Agents. AIED (1) Manh Hung Nguyen, Victor-Alexandru Padurean, Alkis Gotovos, Sebastian Tschiatschek, Adish Singla
2025	J	`jnl`	Synthesizing High-Quality Programming Tasks with LLM-based Expert and Student Agents. CoRR Manh Hung Nguyen, Victor-Alexandru Padurean, Alkis Gotovos, Sebastian Tschiatschek, Adish Singla
2025	J	`jnl`	Understanding and Improving Hyperbolic Deep Reinforcement Learning. CoRR Timo Klein, Thomas Lang, Andrii Shkabrii, Alexander Sturm, Kevin Sidak, Lukas Miklautz, Claudia Plant, Yllka Velaj, Sebastian Tschiatschek
2024	J	`jnl`	Breaking the Reclustering Barrier in Centroid-based Deep Clustering. CoRR Lukas Miklautz, Timo Klein, Kevin Sidak, Collin Leiber, Thomas Lang, Andrii Shkabrii, Sebastian Tschiatschek, Claudia Plant
2024	J	`jnl`	Challenging the Human-in-the-loop in Algorithmic Decision-making. CoRR Sebastian Tschiatschek, Eugenia Stamboliev, Timothée Schmude, Mark Coeckelbergh, Laura Koesten
2024	J	`jnl`	Deliberative XAI: How Explanations Impact Understanding and Decision-Making of AI Novices in Collective and Individual Settings. CoRR Timothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek
2024	J	`jnl`	Information That Matters: Exploring Information Needs of People Affected by Algorithmic Decisions. CoRR Timothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek
2024	B	`conf`	Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming. EDM Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla
2024	A	`conf`	Learning Safety Constraints from Demonstrations with Unknown Rewards. AISTATS David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
2024	J	`jnl`	Plasticity Loss in Deep Reinforcement Learning: A Survey. CoRR Timo Klein, Lukas Miklautz, Kevin Sidak, Claudia Plant, Sebastian Tschiatschek
2024	J	`jnl`	Resource-Efficient Neural Networks for Embedded Systems. J. Mach. Learn. Res. Wolfgang Roth, Günther Schindler, Bernhard Klein, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani
2023	J	`jnl`	Active Third-Person Imitation Learning. CoRR Timo Klein, Susanna Weinberger, Adish Singla, Sebastian Tschiatschek
2023	J	`jnl`	Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes. CoRR Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla
2023	J	`jnl`	Applying Interdisciplinary Frameworks to Understand Algorithmic Decision-Making. CoRR Timothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek
2023	J	`jnl`	Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming from One-Shot Observation. CoRR Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla
2023	A	`conf`	Learning Constraints From Human Stop-Feedback in Reinforcement Learning. AAMAS Silvia Poletti, Alberto Testolin, Sebastian Tschiatschek
2023	J	`jnl`	Learning Safety Constraints from Demonstrations with Unknown Rewards. CoRR David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
2023	—	`conf`	On the Impact of Explanations on Understanding of Algorithmic Decision-Making. FAccT Timothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek
2023	J	`jnl`	On the Impact of Explanations on Understanding of Algorithmic Decision-Making. CoRR Timothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek
2023	—	`conf`	Posterior Consistency for Missing Data in Variational Autoencoders. ECML/PKDD (2) Timur Sudak, Sebastian Tschiatschek
2023	J	`jnl`	Posterior Consistency for Missing Data in Variational Autoencoders. CoRR Timur Sudak, Sebastian Tschiatschek
2023	—	`ed.`	Proceedings of the IJCAI-23 Joint Workshop on Artificial Intelligence Safety and Safe Reinforcement Learning (AISafety-SafeRL 2023) co-located with the 32nd International Joint Conference on Artificial Intelligence(IJCAI2023), Macau, China, August 21-22, 2023. AISafety/SafeRL@IJCAI Gabriel Pedroza, Xiaowei Huang, Xin Cynthia Chen, Andreas Theodorou, Huáscar Espinoza, Nikolaos Matragkas, José Hernández-Orallo, Mauricio Castillo-Effen, Richard Mallah, John A. McDermid, David M. Bossens, Bettina Könighofer, Sebastian Tschiatschek, Anqi Liu
2023	J	`jnl`	Replication Robust Payoff Allocation in Submodular Cooperative Games. IEEE Trans. Artif. Intell. Dongge Han, Michael J. Wooldridge, Alex Rogers, Olga Ohrimenko, Sebastian Tschiatschek
2023	A	`conf`	Specifying Prior Beliefs over DAGs in Deep Bayesian Causal Structure Learning. ECAI Simon Rittel, Sebastian Tschiatschek
2022	—	`conf`	Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes. AIED (1) Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla
2022	B	`conf`	Equity and Fairness of Bayesian Knowledge Tracing. EDM Sebastian Tschiatschek, Maria Knobelsdorf, Adish Singla
2022	J	`jnl`	Equity and Fairness of Bayesian Knowledge Tracing. CoRR Sebastian Tschiatschek, Maria Knobelsdorf, Adish Singla
2022	A*	`conf`	Interactively Learning Preference Constraints in Linear Bandits. ICML David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
2022	J	`jnl`	Interactively Learning Preference Constraints in Linear Bandits. CoRR David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
2022	A*	`conf`	Option Transfer and SMDP Abstraction with Successor Features. IJCAI Dongge Han, Sebastian Tschiatschek
2021	J	`jnl`	Contextual HyperNetworks for Novel Feature Adaptation. CoRR Angus Lamb, Evgeny Saveliev, Yingzhen Li, Sebastian Tschiatschek, Camilla Longden, Simon Woodhead, José Miguel Hernández-Lobato, Richard E. Turner, Pashmina Cameron, Cheng Zhang
2021	A*	`conf`	Details (Don't) Matter: Isolating Cluster Information in Deep Embedded Spaces. IJCAI Lukas Miklautz, Lena G. M. Bauer, Dominik Mautz, Sebastian Tschiatschek, Christian Böhm, Claudia Plant
2021	A*	`conf`	Educational Question Mining At Scale: Prediction, Analysis and Personalization. AAAI Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Simon Peyton Jones, Richard G. Baraniuk, Cheng Zhang
2021	A*	`conf`	Information Directed Reward Learning for Reinforcement Learning. NeurIPS David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause
2021	J	`jnl`	Information Directed Reward Learning for Reinforcement Learning. CoRR David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause
2021	J	`jnl`	MDP Abstraction with Successor Features. CoRR Dongge Han, Michael J. Wooldridge, Sebastian Tschiatschek
2021	A*	`conf`	Sequential Generative Exploration Model for Partially Observable Reinforcement Learning. AAAI Haiyan Yin, Jianda Chen, Sinno Jialin Pan, Sebastian Tschiatschek
2021	A*	`conf`	Social Sensemaking with AI: Designing an Open-ended AI Experience with a Blind Child. CHI Cecily Morrison, Edward Cutrell, Martin Grayson, Anja Thieme, Alex S. Taylor, Geert Roumen, Camilla Longden, Sebastian Tschiatschek, Rita Faia Marques, Abigail Sellen
2020	A*	`conf`	AMRL: Aggregated Memory For Reinforcement Learning. ICLR Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann
2020	J	`jnl`	Large-Scale Educational Question Analysis with Partial Variational Auto-encoders. CoRR Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Simon Peyton Jones, Cheng Zhang
2020	J	`jnl`	Reinforcement Learning with Efficient Active Feature Acquisition. CoRR Haiyan Yin, Yingzhen Li, Sinno Jialin Pan, Cheng Zhang, Sebastian Tschiatschek
2020	J	`jnl`	Replication-Robust Payoff-Allocation with Applications in Machine Learning Marketplaces. CoRR Dongge Han, Shruti Tople, Alex Rogers, Michael J. Wooldridge, Olga Ohrimenko, Sebastian Tschiatschek
2020	J	`jnl`	Resource-Efficient Neural Networks for Embedded Systems. CoRR Wolfgang Roth, Günther Schindler, Matthias Zöhrer, Lukas Pfeifenberger, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani
2020	A	`conf`	Towards Deployment of Robust Cooperative AI Agents: An Algorithmic Framework for Learning Adaptive Policies. AAMAS Ahana Ghosh, Sebastian Tschiatschek, Hamed Mahdavi, Adish Singla
2020	A*	`conf`	VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data. NeurIPS Chao Ma, Sebastian Tschiatschek, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
2020	J	`jnl`	VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data. CoRR Chao Ma, Sebastian Tschiatschek, José Miguel Hernández-Lobato, Richard E. Turner, Cheng Zhang
2019	J	`jnl`	Collaborative Machine Learning Markets with Data-Replication-Robust Payments. CoRR Olga Ohrimenko, Shruti Tople, Sebastian Tschiatschek
2019	A*	`conf`	EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. ICML Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández-Lobato, Sebastian Nowozin, Cheng Zhang
2019	—	`conf`	Evaluating Rule-based Programming and ReinforcementLearning for Personalising an Intelligent System. IUI Workshops Ruixue Liu, Advait Sarkar, Erin Solovey, Sebastian Tschiatschek
2019	A*	`conf`	Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck. NeurIPS Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
2019	J	`jnl`	Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck. CoRR Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
2019	—	`conf`	HM-VAEs: a Deep Generative Model for Real-valued Data with Heterogeneous Marginals. AABI Chao Ma, Sebastian Tschiatschek, Yingzhen Li, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
2019	J	`jnl`	Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model. CoRR Wenbo Gong, Sebastian Tschiatschek, Richard E. Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang
2019	A*	`conf`	Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model. NeurIPS Wenbo Gong, Sebastian Tschiatschek, Sebastian Nowozin, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
2019	A*	`conf`	Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints. NeurIPS Sebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla
2019	J	`jnl`	Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints. CoRR Sebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla
2019	A*	`conf`	Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning. NeurIPS David Janz, Jiri Hron, Przemyslaw Mazur, Katja Hofmann, José Miguel Hernández-Lobato, Sebastian Tschiatschek
2019	J	`jnl`	Towards Deployment of Robust AI Agents for Human-Machine Partnerships. CoRR Ahana Ghosh, Sebastian Tschiatschek, Hamed Mahdavi, Adish Singla
2018	A*	`conf`	Differentiable Submodular Maximization. IJCAI Sebastian Tschiatschek, Aytunc Sahin, Andreas Krause
2018	J	`jnl`	Differentiable Submodular Maximization. CoRR Sebastian Tschiatschek, Aytunc Sahin, Andreas Krause
2018	J	`jnl`	EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. CoRR Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández-Lobato, Sebastian Nowozin, Cheng Zhang
2018	J	`jnl`	Efficient and Robust Machine Learning for Real-World Systems. CoRR Franz Pernkopf, Wolfgang Roth, Matthias Zöhrer, Lukas Pfeifenberger, Günther Schindler, Holger Fröning, Sebastian Tschiatschek, Robert Peharz, Matthew Mattina, Zoubin Ghahramani
2018	—	`conf`	Fake News Detection in Social Networks via Crowd Signals. WWW (Companion Volume) Sebastian Tschiatschek, Adish Singla, Manuel Gomez-Rodriguez, Arpit Merchant, Andreas Krause
2018	J	`jnl`	Hybrid generative-discriminative training of Gaussian mixture models. Pattern Recognit. Lett. Wolfgang Roth, Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf
2018	A*	`conf`	Learning User Preferences to Incentivize Exploration in the Sharing Economy. AAAI Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause
2018	J	`jnl`	Successor Uncertainties: exploration and uncertainty in temporal difference learning. CoRR David Janz, Jiri Hron, José Miguel Hernández-Lobato, Katja Hofmann, Sebastian Tschiatschek
2018	J	`jnl`	Sum-Product Networks for Sequence Labeling. CoRR Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf
2018	A*	`conf`	Teaching Inverse Reinforcement Learners via Features and Demonstrations. NeurIPS Luis Haug, Sebastian Tschiatschek, Adish Singla
2018	J	`jnl`	Teaching Inverse Reinforcement Learners via Features and Demonstrations. CoRR Luis Haug, Sebastian Tschiatschek, Adish Singla
2018	J	`jnl`	Variational Inference for Data-Efficient Model Learning in POMDPs. CoRR Sebastian Tschiatschek, Kai Arulkumaran, Jan Stühmer, Katja Hofmann
2017	J	`jnl`	Coordinated Online Learning With Applications to Learning User Preferences. CoRR Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause
2017	J	`jnl`	Detecting Fake News in Social Networks via Crowdsourcing. CoRR Sebastian Tschiatschek, Adish Singla, Manuel Gomez-Rodriguez, Arpit Merchant, Andreas Krause
2017	A	`conf`	Frame and Segment Level Recurrent Neural Networks for Phone Classification. INTERSPEECH Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf
2017	A*	`conf`	Guarantees for Greedy Maximization of Non-submodular Functions with Applications. ICML Andrew An Bian, Joachim M. Buhmann, Andreas Krause, Sebastian Tschiatschek
2017	J	`jnl`	Guarantees for Greedy Maximization of Non-submodular Functions with Applications. CoRR Andrew An Bian, Joachim M. Buhmann, Andreas Krause, Sebastian Tschiatschek
2017	A	`conf`	Improving Optimization-Based Approximate Inference by Clamping Variables. UAI Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause
2017	J	`jnl`	Learning User Preferences to Incentivize Exploration in the Sharing Economy. CoRR Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause
2017	A*	`conf`	Selecting Sequences of Items via Submodular Maximization. AAAI Sebastian Tschiatschek, Adish Singla, Andreas Krause
2016	A*	`conf`	Actively Learning Hemimetrics with Applications to Eliciting User Preferences. ICML Adish Singla, Sebastian Tschiatschek, Andreas Krause
2016	J	`jnl`	Actively Learning Hemimetrics with Applications to Eliciting User Preferences. CoRR Adish Singla, Sebastian Tschiatschek, Andreas Krause
2016	—	`conf`	Cooperative Graphical Models. NIPS Josip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek, Andreas Krause
2016	A	`conf`	Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation. AISTATS Sebastian Tschiatschek, Josip Djolonga, Andreas Krause
2016	A*	`conf`	Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization. AAAI Adish Singla, Sebastian Tschiatschek, Andreas Krause
2016	—	`conf`	Variational Inference in Mixed Probabilistic Submodular Models. NIPS Josip Djolonga, Sebastian Tschiatschek, Andreas Krause
2016	A	`conf`	Virtual Adversarial Training Applied to Neural Higher-Order Factors for Phone Classification. INTERSPEECH Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf
2015	—	`conf`	Message Scheduling Methods for Belief Propagation. ECML/PKDD (2) Christian Knoll, Michael Rath, Sebastian Tschiatschek, Franz Pernkopf
2015	A	`conf`	Neural higher-order factors in conditional random fields for phoneme classification. INTERSPEECH Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf
2015	J	`jnl`	Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization. CoRR Adish Singla, Sebastian Tschiatschek, Andreas Krause
2015	J	`jnl`	On Bayesian Network Classifiers with Reduced Precision Parameters. IEEE Trans. Pattern Anal. Mach. Intell. Sebastian Tschiatschek, Franz Pernkopf
2015	A	`conf`	On Theoretical Properties of Sum-Product Networks. AISTATS Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf, Pedro M. Domingos
2015	—	`conf`	Parameter Learning of Bayesian Network Classifiers Under Computational Constraints. ECML/PKDD (1) Sebastian Tschiatschek, Franz Pernkopf
2015	—	`conf`	Structured Regularizer for Neural Higher-Order Sequence Models. ECML/PKDD (1) Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf
2014	—	`conf`	Integer Bayesian Network Classifiers. ECML/PKDD (3) Sebastian Tschiatschek, Karin Paul, Franz Pernkopf
2014	—	`conf`	Learning Mixtures of Submodular Functions for Image Collection Summarization. NIPS Sebastian Tschiatschek, Rishabh K. Iyer, Haochen Wei, Jeff A. Bilmes
2013	Misc	`conf`	Bounds for Bayesian network classifiers with reduced precision parameters. ICASSP Sebastian Tschiatschek, Carlos Eduardo Cancino-Chacón, Franz Pernkopf
2013	A	`conf`	On the Asymptotic Optimality of Maximum Margin Bayesian Networks. AISTATS Sebastian Tschiatschek, Franz Pernkopf
2013	—	`conf`	The Most Generative Maximum Margin Bayesian Networks. ICML (3) Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf
2012	—	`conf`	Bayesian Network Classifiers with Reduced Precision Parameters. ECML/PKDD (1) Sebastian Tschiatschek, Peter Reinprecht, Manfred Mücke, Franz Pernkopf
2012	—	`conf`	Convex Combinations of Maximum Margin Bayesian Network Classifiers. ICPRAM (1) Sebastian Tschiatschek, Franz Pernkopf
2012	—	`conf`	Handling missing features in maximum margin Bayesian network classifiers. MLSP Sebastian Tschiatschek, Nikolaus Mutsam, Franz Pernkopf
2012	J	`jnl`	Maximum Margin Bayesian Network Classifiers. IEEE Trans. Pattern Anal. Mach. Intell. Franz Pernkopf, Michael Wohlmayr, Sebastian Tschiatschek