Sebastian Tschiatschek

Orcid: 0000-0002-2592-0108

Affiliations:
  • University of Vienna, Austria


According to our database1, Sebastian Tschiatschek authored at least 74 papers between 2012 and 2024.

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Bibliography

2024
Information That Matters: Exploring Information Needs of People Affected by Algorithmic Decisions.
CoRR, 2024

2023
Replication Robust Payoff Allocation in Submodular Cooperative Games.
IEEE Trans. Artif. Intell., October, 2023

Active Third-Person Imitation Learning.
CoRR, 2023

Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming from One-Shot Observation.
CoRR, 2023

Applying Interdisciplinary Frameworks to Understand Algorithmic Decision-Making.
CoRR, 2023

Learning Safety Constraints from Demonstrations with Unknown Rewards.
CoRR, 2023

Posterior Consistency for Missing Data in Variational Autoencoders.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

On the Impact of Explanations on Understanding of Algorithmic Decision-Making.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Specifying Prior Beliefs over DAGs in Deep Bayesian Causal Structure Learning.
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.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022
Option Transfer and SMDP Abstraction with Successor Features.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Interactively Learning Preference Constraints in Linear Bandits.
Proceedings of the International Conference on Machine Learning, 2022

Equity and Fairness of Bayesian Knowledge Tracing.
Proceedings of the 15th International Conference on Educational Data Mining, 2022

Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes.
Proceedings of the Artificial Intelligence in Education - 23rd International Conference, 2022

2021
MDP Abstraction with Successor Features.
CoRR, 2021

Contextual HyperNetworks for Novel Feature Adaptation.
CoRR, 2021

Information Directed Reward Learning for Reinforcement Learning.
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.
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.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

Sequential Generative Exploration Model for Partially Observable Reinforcement Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Educational Question Mining At Scale: Prediction, Analysis and Personalization.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Reinforcement Learning with Efficient Active Feature Acquisition.
CoRR, 2020

Replication-Robust Payoff-Allocation with Applications in Machine Learning Marketplaces.
CoRR, 2020

Large-Scale Educational Question Analysis with Partial Variational Auto-encoders.
CoRR, 2020

Resource-Efficient Neural Networks for Embedded Systems.
CoRR, 2020

VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data.
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.
Proceedings of the 8th International Conference on Learning Representations, 2020

Towards Deployment of Robust Cooperative AI Agents: An Algorithmic Framework for Learning Adaptive Policies.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019
Collaborative Machine Learning Markets with Data-Replication-Robust Payments.
CoRR, 2019

Towards Deployment of Robust AI Agents for Human-Machine Partnerships.
CoRR, 2019

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model.
CoRR, 2019

Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints.
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.
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.
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.
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.
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.
Proceedings of the 36th International Conference on Machine Learning, 2019

HM-VAEs: a Deep Generative Model for Real-valued Data with Heterogeneous Marginals.
Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2019

2018
Hybrid generative-discriminative training of Gaussian mixture models.
Pattern Recognit. Lett., 2018

Efficient and Robust Machine Learning for Real-World Systems.
CoRR, 2018

Successor Uncertainties: exploration and uncertainty in temporal difference learning.
CoRR, 2018

Sum-Product Networks for Sequence Labeling.
CoRR, 2018

Variational Inference for Data-Efficient Model Learning in POMDPs.
CoRR, 2018

Fake News Detection in Social Networks via Crowd Signals.
Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Teaching Inverse Reinforcement Learners via Features and Demonstrations.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Differentiable Submodular Maximization.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Learning User Preferences to Incentivize Exploration in the Sharing Economy.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Detecting Fake News in Social Networks via Crowdsourcing.
CoRR, 2017

Coordinated Online Learning With Applications to Learning User Preferences.
CoRR, 2017

Improving Optimization-Based Approximate Inference by Clamping Variables.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Frame and Segment Level Recurrent Neural Networks for Phone Classification.
Proceedings of the Interspeech 2017, 2017

Guarantees for Greedy Maximization of Non-submodular Functions with Applications.
Proceedings of the 34th International Conference on Machine Learning, 2017

Selecting Sequences of Items via Submodular Maximization.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Variational Inference in Mixed Probabilistic Submodular Models.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Cooperative Graphical Models.
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.
Proceedings of the Interspeech 2016, 2016

Actively Learning Hemimetrics with Applications to Eliciting User Preferences.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation.
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.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
On Bayesian Network Classifiers with Reduced Precision Parameters.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Parameter Learning of Bayesian Network Classifiers Under Computational Constraints.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Structured Regularizer for Neural Higher-Order Sequence Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Message Scheduling Methods for Belief Propagation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Neural higher-order factors in conditional random fields for phoneme classification.
Proceedings of the INTERSPEECH 2015, 2015

On Theoretical Properties of Sum-Product Networks.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Integer Bayesian Network Classifiers.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Learning Mixtures of Submodular Functions for Image Collection Summarization.
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.
Proceedings of the 30th International Conference on Machine Learning, 2013

Bounds for Bayesian network classifiers with reduced precision parameters.
Proceedings of the IEEE International Conference on Acoustics, 2013

On the Asymptotic Optimality of Maximum Margin Bayesian Networks.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Maximum Margin Bayesian Network Classifiers.
IEEE Trans. Pattern Anal. Mach. Intell., 2012

Bayesian Network Classifiers with Reduced Precision Parameters.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Handling missing features in maximum margin Bayesian network classifiers.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Convex Combinations of Maximum Margin Bayesian Network Classifiers.
Proceedings of the ICPRAM 2012, 2012


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