Sebastian Tschiatschek

发表

Handling missing features in maximum margin Bayesian network classifiers

Sebastian Tschiatschek, Nikolaus Mutsam, Franz Pernkopf, 2012, 2012 IEEE International Workshop on Machine Learning for Signal Processing.

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

Sebastian Tschiatschek, Zichao Wang, Simon Woodhead, 2020, ArXiv.

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

Sebastian Nowozin, Sebastian Tschiatschek, Cheng Zhang, 2019, ArXiv.

Discriminative Bayesian Network Classiers with Reduced Precision Parameters

Sebastian Tschiatschek, Franz Pernkopf, Manfred Mücke, 2012 .

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

Andreas Krause, Sebastian Tschiatschek, Adish Singla, 2015, AAAI.

Differentiable Submodular Maximization

Andreas Krause, Sebastian Tschiatschek, Aytunc Sahin, 2018, IJCAI.

Detecting Fake News in Social Networks via Crowdsourcing pdf

Sebastian Tschiatschek, Adish Singla, Andreas Krause, 2017, ArXiv.

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

Sebastian Tschiatschek, Franz Pernkopf, Martin Ratajczak, 2015, INTERSPEECH.

Efficient and Robust Machine Learning for Real-World Systems pdf

Holger Fröning, Sebastian Tschiatschek, Franz Pernkopf, 2018, ArXiv.

Convex Combinations of Maximum Margin Bayesian Network Classifiers

Sebastian Tschiatschek, Franz Pernkopf, F. Pernkopf, 2012, ICPRAM.

Frame and Segment Level Recurrent Neural Networks for Phone Classification

Sebastian Tschiatschek, Franz Pernkopf, Martin Ratajczak, 2017, INTERSPEECH.

Teaching Inverse Reinforcement Learners via Features and Demonstrations

Sebastian Tschiatschek, Adish Singla, Luis Haug, 2018, NeurIPS.

Fake News Detection in Social Networks via Crowd Signals

Sebastian Tschiatschek, Adish Singla, Andreas Krause, 2017, WWW.

Sum-Product Networks for Structured Prediction: Context-Specific Deep Conditional Random Fields

Sebastian Tschiatschek, Franz Pernkopf, Martin Ratajczak, 2014 .

Coordinated Online Learning With Applications to Learning User Preferences pdf

Andreas Krause, Sebastian Tschiatschek, Adish Singla, 2017, ArXiv.

On Reduced Precision Bayesian Network Classifiers.

Sebastian Tschiatschek, Franz Pernkopf, 2015 .

Successor Uncertainties: exploration and uncertainty in temporal difference learning

Sebastian Tschiatschek, David Janz, José Miguel Hernández-Lobato, 2018, NeurIPS.

Structured Regularizer for Neural Higher-Order Sequence Models

Sebastian Tschiatschek, Franz Pernkopf, Martin Ratajczak, 2015, ECML/PKDD.

The Most Generative Maximum Margin Bayesian Networks

Sebastian Tschiatschek, Franz Pernkopf, Robert Peharz, 2013, ICML.

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

Sebastian Tschiatschek, Adish Singla, Ahana Ghosh, 2020, AAMAS.

Bayesian Network Classifiers with Reduced Precision Parameters

Sebastian Tschiatschek, Franz Pernkopf, Manfred Mücke, 2012, ECML/PKDD.

Improving Optimization-Based Approximate Inference by Clamping Variables

Andreas Krause, Sebastian Tschiatschek, Josip Djolonga, 2017, UAI.

Hybrid generative-discriminative training of Gaussian mixture models

Sebastian Tschiatschek, Franz Pernkopf, Robert Peharz, 2018, Pattern Recognit. Lett..

On Bayesian Network Classifiers with Reduced Precision Parameters

Sebastian Tschiatschek, Franz Pernkopf, F. Pernkopf, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

On the Asymptotic Optimality of Maximum Margin Bayesian Networks

Sebastian Tschiatschek, Franz Pernkopf, F. Pernkopf, 2013, AISTATS.

Resource-Efficient Neural Networks for Embedded Systems pdf

Sebastian Tschiatschek, Franz Pernkopf, Robert Peharz, 2020, ArXiv.

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

Sebastian Tschiatschek, Adish Singla, Ahana Ghosh, 2019, NeurIPS.

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

Sebastian Tschiatschek, Adish Singla, Ahana Ghosh, 2019, ArXiv.

Bayesian EDDI: Sequential Variable Selection with Bayesian Partial VAE

Sebastian Nowozin, Sebastian Tschiatschek, Cheng Zhang, 2019 .

Actively Learning Hemimetrics with Applications to Eliciting User Preferences pdf

Andreas Krause, Sebastian Tschiatschek, Adish Singla, 2016, ICML.

Variational Inference for Data-Efficient Model Learning in POMDPs pdf

Katja Hofmann, Sebastian Tschiatschek, Kai Arulkumaran, 2018, ArXiv.

Selecting Sequences of Items via Submodular Maximization

Andreas Krause, Sebastian Tschiatschek, Adish Singla, 2017, AAAI.

Message Scheduling Methods for Belief Propagation

Sebastian Tschiatschek, Franz Pernkopf, Michael Rath, 2015, ECML/PKDD.

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

Sebastian Tschiatschek, Cheng Zhang, Richard E. Turner, 2019, AABI.

Generatively Optimized Bayesian Network Classifiers Under Computational Constraints

Sebastian Tschiatschek, Franz Pernkopf, 2015 .

Integer Bayesian Networks

Sebastian Tschiatschek, Franz Pernkopf, Karin Paul, 2014 .

Collaborative Machine Learning Markets

Sebastian Tschiatschek, Shruti Tople, Olga Ohrimenko, 2020 .

AMRL: Aggregated Memory For Reinforcement Learning

Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, 2020, ICLR.

Learning User Preferences to Incentivize Exploration in the Sharing Economy pdf

Andreas Krause, Sebastian Tschiatschek, Adish Singla, 2017, AAAI.

Reinforcement Learning with Efficient Active Feature Acquisition pdf

Sebastian Tschiatschek, Cheng Zhang, Sinno Jialin Pan, 2020, ArXiv.

Cooperative Graphical Models

Andreas Krause, Sebastian Tschiatschek, Stefanie Jegelka, 2016, NIPS.

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

Sebastian Tschiatschek, Franz Pernkopf, Martin Ratajczak, 2016, INTERSPEECH.

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

Sebastian Nowozin, Sebastian Tschiatschek, Cheng Zhang, 2019, NeurIPS.

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

Andreas Krause, Joachim M. Buhmann, Sebastian Tschiatschek, 2017, ICML.

Context-Specic Deep Conditional Random Fields for Structured Prediction

Sebastian Tschiatschek, Franz Pernkopf, Martin Ratajczak, 2014 .

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

Sebastian Tschiatschek, Advait Sarkar, Ruixue Liu, 2019, IUI Workshops.

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

Sebastian Tschiatschek, Alex Rogers, Shruti Tople, 2020, ArXiv.

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

Sebastian Tschiatschek, Cheng Zhang, Richard E. Turner, 2020, NeurIPS.

Sum-Product Networks for Sequence Labeling pdf

Sebastian Tschiatschek, Franz Pernkopf, Martin Ratajczak, 2018, ArXiv.

Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation

Andreas Krause, Sebastian Tschiatschek, Josip Djolonga, 2016, AISTATS.

Bounds for Bayesian network classifiers with reduced precision parameters

Sebastian Tschiatschek, Franz Pernkopf, Carlos Eduardo Cancino Chacón, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck

Sam Devlin, Sebastian Tschiatschek, Katja Hofmann, 2019, NeurIPS.

Parameter Learning of Bayesian Network Classifiers Under Computational Constraints

Sebastian Tschiatschek, Franz Pernkopf, F. Pernkopf, 2015, ECML/PKDD.

Variational Inference in Mixed Probabilistic Submodular Models

Andreas Krause, Sebastian Tschiatschek, Josip Djolonga, 2016, NIPS.

Introduction to Probabilistic Graphical Models

Sebastian Tschiatschek, Franz Pernkopf, Robert Peharz, 2014 .

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

Sebastian Nowozin, Sebastian Tschiatschek, Cheng Zhang, 2018, ICML.

Learning Mixtures of Submodular Functions for Image Collection Summarization

Rishabh K. Iyer, Sebastian Tschiatschek, Jeff A. Bilmes, 2014, NIPS.

On Theoretical Properties of Sum-Product Networks

Sebastian Tschiatschek, Franz Pernkopf, Pedro M. Domingos, 2015, AISTATS.

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

Sebastian Tschiatschek, Shruti Tople, Olga Ohrimenko, 2019, ArXiv.

Integer Bayesian Network Classifiers

Sebastian Tschiatschek, Franz Pernkopf, Karin Paul, 2014, ECML/PKDD.

Maximum Margin Bayesian Network Classifiers

Sebastian Tschiatschek, Franz Pernkopf, Michael Wohlmayr, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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

Sebastian Tschiatschek, Abigail Sellen, Edward Cutrell, 2021, CHI.

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

Sebastian Tschiatschek, Claudia Plant, Lukas Miklautz, 2021, IJCAI.

Educational Question Mining At Scale: Prediction, Analysis and Personalization

Sebastian Tschiatschek, Zichao Wang, Richard G. Baraniuk, 2021, AAAI.

Contextual HyperNetworks for Novel Feature Adaptation pdf

Sebastian Tschiatschek, Richard E. Turner, Angus Lamb, 2021, ArXiv.

MDP Abstraction with Successor Features pdf

Sebastian Tschiatschek, Michael Wooldridge, Dongge Han, 2021, ArXiv.

Sequential Generative Exploration Model for Partially Observable Reinforcement Learning

Sebastian Tschiatschek, Sinno Jialin Pan, Haiyan Yin, 2021, AAAI.

Information Directed Reward Learning for Reinforcement Learning pdf

Sebastian Tschiatschek, Andreas Krause, Matteo Turchetta, 2021, ArXiv.

Quantum-classical truncated Newton method for high-dimensional energy landscapes

Sebastian Tschiatschek, Leonard Wossnig, Stefan Zohren, 2017, 1710.07063.