Ziebart, Brian

16 publications

NeurIPS 2023 Distributionally Robust Skeleton Learning of Discrete Bayesian Networks Yeshu Li, Brian Ziebart
AISTATS 2022 Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks Yeshu Li, Zhan Shi, Xinhua Zhang, Brian Ziebart
NeurIPS 2022 Moment Distributionally Robust Tree Structured Prediction Yeshu Li, Danyal Saeed, Xinhua Zhang, Brian Ziebart, Kevin Gimpel
ICML 2022 Towards Uniformly Superhuman Autonomy via Subdominance Minimization Brian Ziebart, Sanjiban Choudhury, Xinyan Yan, Paul Vernaza
NeurIPS 2021 Distributionally Robust Imitation Learning Mohammad Ali Bashiri, Brian Ziebart, Xinhua Zhang
UAI 2020 Adversarial Learning for 3D Matching Wei Xing, Brian Ziebart
ICML 2019 Active Learning for Probabilistic Structured Prediction of Cuts and Matchings Sima Behpour, Anqi Liu, Brian Ziebart
NeurIPS 2018 Distributionally Robust Graphical Models Rizal Fathony, Ashkan Rezaei, Mohammad Ali Bashiri, Xinhua Zhang, Brian Ziebart
ICML 2018 Efficient and Consistent Adversarial Bipartite Matching Rizal Fathony, Sima Behpour, Xinhua Zhang, Brian Ziebart
NeurIPS 2018 Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes Andrea Tirinzoni, Marek Petrik, Xiangli Chen, Brian Ziebart
NeurIPS 2017 Adversarial Surrogate Losses for Ordinal Regression Rizal Fathony, Mohammad Ali Bashiri, Brian Ziebart
NeurIPS 2016 Adversarial Multiclass Classification: A Risk Minimization Perspective Rizal Fathony, Anqi Liu, Kaiser Asif, Brian Ziebart
NeurIPS 2015 Adversarial Prediction Games for Multivariate Losses Hong Wang, Wei Xing, Kaiser Asif, Brian Ziebart
NeurIPS 2015 Softstar: Heuristic-Guided Probabilistic Inference Mathew Monfort, Brenden M Lake, Brenden M Lake, Brian Ziebart, Patrick Lucey, Josh Tenenbaum
NeurIPS 2014 Robust Classification Under Sample Selection Bias Anqi Liu, Brian Ziebart
AISTATS 2009 Inverse Optimal Heuristic Control for Imitation Learning Nathan Ratliff, Brian Ziebart, Kevin Peterson, J. Andrew Bagnell, Martial Hebert, Anind K. Dey, Siddhartha Srinivasa