Sebastian Tschiatschek

According to our database, Sebastian Tschiatschek authored at least 77 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Resource-Efficient Neural Networks for Embedded Systems.

Wolfgang Roth, Günther Schindler, Bernhard Klein, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani

J. Mach. Learn. Res., 2024

Challenging the Human-in-the-loop in Algorithmic Decision-making.

Sebastian Tschiatschek, Eugenia Stamboliev, Timothée Schmude, Mark Coeckelbergh, Laura Koesten

CoRR, 2024

Information That Matters: Exploring Information Needs of People Affected by Algorithmic Decisions.

Timothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek

CoRR, 2024

Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming.

Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla

Proceedings of the 17th International Conference on Educational Data Mining, 2024

Learning Safety Constraints from Demonstrations with Unknown Rewards.

David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Replication Robust Payoff Allocation in Submodular Cooperative Games.

Dongge Han, Michael J. Wooldridge, Alex Rogers, Olga Ohrimenko, Sebastian Tschiatschek

IEEE Trans. Artif. Intell., October, 2023

Active Third-Person Imitation Learning.

Timo Klein, Susanna Weinberger, Adish Singla, Sebastian Tschiatschek

CoRR, 2023

Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming from One-Shot Observation.

Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla

CoRR, 2023

Applying Interdisciplinary Frameworks to Understand Algorithmic Decision-Making.

Timothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek

CoRR, 2023

Posterior Consistency for Missing Data in Variational Autoencoders.

Timur Sudak, Sebastian Tschiatschek

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

On the Impact of Explanations on Understanding of Algorithmic Decision-Making.

Timothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Specifying Prior Beliefs over DAGs in Deep Bayesian Causal Structure Learning.

Simon Rittel, Sebastian Tschiatschek

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Learning Constraints From Human Stop-Feedback in Reinforcement Learning.

Silvia Poletti, Alberto Testolin, Sebastian Tschiatschek

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

Option Transfer and SMDP Abstraction with Successor Features.

Dongge Han, Sebastian Tschiatschek

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Interactively Learning Preference Constraints in Linear Bandits.

David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause

Proceedings of the International Conference on Machine Learning, 2022

Equity and Fairness of Bayesian Knowledge Tracing.

Sebastian Tschiatschek, Maria Knobelsdorf, Adish Singla

Proceedings of the 15th International Conference on Educational Data Mining, 2022

Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes.

Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla

Proceedings of the Artificial Intelligence in Education - 23rd International Conference, 2022

2021

MDP Abstraction with Successor Features.

Dongge Han, Michael J. Wooldridge, Sebastian Tschiatschek

CoRR, 2021

Contextual HyperNetworks for Novel Feature Adaptation.

Angus Lamb, Evgeny Saveliev, Yingzhen Li, Sebastian Tschiatschek, Camilla Longden, Simon Woodhead, José Miguel Hernández-Lobato, Richard E. Turner, Pashmina Cameron, Cheng Zhang

CoRR, 2021

Information Directed Reward Learning for Reinforcement Learning.

David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Details (Don't) Matter: Isolating Cluster Information in Deep Embedded Spaces.

Lukas Miklautz, Lena G. M. Bauer, Dominik Mautz, Sebastian Tschiatschek, Christian Böhm, Claudia Plant

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Social Sensemaking with AI: Designing an Open-ended AI Experience with a Blind Child.

Cecily Morrison, Edward Cutrell, Martin Grayson, Anja Thieme, Alex S. Taylor, Geert Roumen, Camilla Longden, Sebastian Tschiatschek, Rita Faia Marques, Abigail Sellen

Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

Sequential Generative Exploration Model for Partially Observable Reinforcement Learning.

Haiyan Yin, Jianda Chen, Sinno Jialin Pan, Sebastian Tschiatschek

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Educational Question Mining At Scale: Prediction, Analysis and Personalization.

Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Simon Peyton Jones, Richard G. Baraniuk, Cheng Zhang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Reinforcement Learning with Efficient Active Feature Acquisition.

Haiyan Yin, Yingzhen Li, Sinno Jialin Pan, Cheng Zhang, Sebastian Tschiatschek

CoRR, 2020

Replication-Robust Payoff-Allocation with Applications in Machine Learning Marketplaces.

Dongge Han, Shruti Tople, Alex Rogers, Michael J. Wooldridge, Olga Ohrimenko, Sebastian Tschiatschek

CoRR, 2020

Large-Scale Educational Question Analysis with Partial Variational Auto-encoders.

Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Simon Peyton Jones, Cheng Zhang

CoRR, 2020

Resource-Efficient Neural Networks for Embedded Systems.

Wolfgang Roth, Günther Schindler, Matthias Zöhrer, Lukas Pfeifenberger, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani

CoRR, 2020

VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data.

Chao Ma, Sebastian Tschiatschek, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

AMRL: Aggregated Memory For Reinforcement Learning.

Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann

Proceedings of the 8th International Conference on Learning Representations, 2020

Towards Deployment of Robust Cooperative AI Agents: An Algorithmic Framework for Learning Adaptive Policies.

Ahana Ghosh, Sebastian Tschiatschek, Hamed Mahdavi, Adish Singla

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

Collaborative Machine Learning Markets with Data-Replication-Robust Payments.

Olga Ohrimenko, Shruti Tople, Sebastian Tschiatschek

CoRR, 2019

Towards Deployment of Robust AI Agents for Human-Machine Partnerships.

Ahana Ghosh, Sebastian Tschiatschek, Hamed Mahdavi, Adish Singla

CoRR, 2019

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model.

Wenbo Gong, Sebastian Tschiatschek, Richard E. Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang

CoRR, 2019

Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints.

Sebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning.

David Janz, Jiri Hron, Przemyslaw Mazur, Katja Hofmann, José Miguel Hernández-Lobato, Sebastian Tschiatschek

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck.

Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model.

Wenbo Gong, Sebastian Tschiatschek, Sebastian Nowozin, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Evaluating Rule-based Programming and ReinforcementLearning for Personalising an Intelligent System.

Ruixue Liu, Advait Sarkar, Erin Solovey, Sebastian Tschiatschek

Proceedings of the Joint Proceedings of the ACM IUI 2019 Workshops co-located with the 24th ACM Conference on Intelligent User Interfaces (ACM IUI 2019), 2019

EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE.

Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández-Lobato, Sebastian Nowozin, Cheng Zhang

Proceedings of the 36th International Conference on Machine Learning, 2019

HM-VAEs: a Deep Generative Model for Real-valued Data with Heterogeneous Marginals.

Chao Ma, Sebastian Tschiatschek, Yingzhen Li, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang

Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2019

2018

Hybrid generative-discriminative training of Gaussian mixture models.

Wolfgang Roth, Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf

Pattern Recognit. Lett., 2018

Efficient and Robust Machine Learning for Real-World Systems.

Franz Pernkopf, Wolfgang Roth, Matthias Zöhrer, Lukas Pfeifenberger, Günther Schindler, Holger Fröning, Sebastian Tschiatschek, Robert Peharz, Matthew Mattina, Zoubin Ghahramani

CoRR, 2018

Successor Uncertainties: exploration and uncertainty in temporal difference learning.

David Janz, Jiri Hron, José Miguel Hernández-Lobato, Katja Hofmann, Sebastian Tschiatschek

CoRR, 2018

Sum-Product Networks for Sequence Labeling.

Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf

CoRR, 2018

Variational Inference for Data-Efficient Model Learning in POMDPs.

Sebastian Tschiatschek, Kai Arulkumaran, Jan Stühmer, Katja Hofmann

CoRR, 2018

Fake News Detection in Social Networks via Crowd Signals.

Sebastian Tschiatschek, Adish Singla, Manuel Gomez-Rodriguez, Arpit Merchant, Andreas Krause

Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Teaching Inverse Reinforcement Learners via Features and Demonstrations.

Luis Haug, Sebastian Tschiatschek, Adish Singla

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Differentiable Submodular Maximization.

Sebastian Tschiatschek, Aytunc Sahin, Andreas Krause

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Learning User Preferences to Incentivize Exploration in the Sharing Economy.

Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Detecting Fake News in Social Networks via Crowdsourcing.

Sebastian Tschiatschek, Adish Singla, Manuel Gomez-Rodriguez, Arpit Merchant, Andreas Krause

CoRR, 2017

Coordinated Online Learning With Applications to Learning User Preferences.

Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause

CoRR, 2017

Improving Optimization-Based Approximate Inference by Clamping Variables.

Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Frame and Segment Level Recurrent Neural Networks for Phone Classification.

Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf

Proceedings of the 18th Annual Conference of the International Speech Communication Association, 2017

Guarantees for Greedy Maximization of Non-submodular Functions with Applications.

Andrew An Bian, Joachim M. Buhmann, Andreas Krause, Sebastian Tschiatschek

Proceedings of the 34th International Conference on Machine Learning, 2017

Selecting Sequences of Items via Submodular Maximization.

Sebastian Tschiatschek, Adish Singla, Andreas Krause

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Variational Inference in Mixed Probabilistic Submodular Models.

Josip Djolonga, Sebastian Tschiatschek, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Cooperative Graphical Models.

Josip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Virtual Adversarial Training Applied to Neural Higher-Order Factors for Phone Classification.

Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf

Proceedings of the 17th Annual Conference of the International Speech Communication Association, 2016

Actively Learning Hemimetrics with Applications to Eliciting User Preferences.

Adish Singla, Sebastian Tschiatschek, Andreas Krause

Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation.

Sebastian Tschiatschek, Josip Djolonga, Andreas Krause

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization.

Adish Singla, Sebastian Tschiatschek, Andreas Krause

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

On Bayesian Network Classifiers with Reduced Precision Parameters.

Sebastian Tschiatschek, Franz Pernkopf

IEEE Trans. Pattern Anal. Mach. Intell., 2015

Parameter Learning of Bayesian Network Classifiers Under Computational Constraints.

Sebastian Tschiatschek, Franz Pernkopf

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Structured Regularizer for Neural Higher-Order Sequence Models.

Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Message Scheduling Methods for Belief Propagation.

Christian Knoll, Michael Rath, Sebastian Tschiatschek, Franz Pernkopf

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Neural higher-order factors in conditional random fields for phoneme classification.

Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf

Proceedings of the 16th Annual Conference of the International Speech Communication Association, 2015

On Theoretical Properties of Sum-Product Networks.

Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf, Pedro M. Domingos

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Integer Bayesian Network Classifiers.

Sebastian Tschiatschek, Karin Paul, Franz Pernkopf

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Learning Mixtures of Submodular Functions for Image Collection Summarization.

Sebastian Tschiatschek, Rishabh K. Iyer, Haochen Wei, Jeff A. Bilmes

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

The Most Generative Maximum Margin Bayesian Networks.

Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf

Proceedings of the 30th International Conference on Machine Learning, 2013

Bounds for Bayesian network classifiers with reduced precision parameters.

Sebastian Tschiatschek, Carlos Eduardo Cancino Chacón, Franz Pernkopf

Proceedings of the IEEE International Conference on Acoustics, 2013

On the Asymptotic Optimality of Maximum Margin Bayesian Networks.

Sebastian Tschiatschek, Franz Pernkopf

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

Maximum Margin Bayesian Network Classifiers.

Franz Pernkopf, Michael Wohlmayr, Sebastian Tschiatschek

IEEE Trans. Pattern Anal. Mach. Intell., 2012

Bayesian Network Classifiers with Reduced Precision Parameters.

Sebastian Tschiatschek, Peter Reinprecht, Manfred Mücke, Franz Pernkopf

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Handling missing features in maximum margin Bayesian network classifiers.

Sebastian Tschiatschek, Nikolaus Mutsam, Franz Pernkopf

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Convex Combinations of Maximum Margin Bayesian Network Classifiers.

Sebastian Tschiatschek, Franz Pernkopf

Proceedings of the ICPRAM 2012, 2012