← Authors

Brian Ziebart

21 papers · 2014–2025 · 7 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (11) 🐝 Cross-Pollinator (11) 🌈 Renaissance Researcher (8) πŸ—ΊοΈ Taxonomy Completionist (50) 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) πŸ† Keyword Champion (3) πŸ’Ž Century Club (21) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (12) πŸ—ƒοΈ Keyword Collector (96)

Conferences

NIPS (10) ICML (3) AISTATS (2) COLING (2) IJCAI (2) AAAI (1) UAI (1)

Top co-authors

Rizal Fathony (5) Xinhua Zhang (5) Yeshu Li (3) Nikolaos Agadakos (3) Mohammad Ali Bashiri (3) Anqi Liu (3) Lisa Sharp (2) Sima Behpour (2) Ashkan Rezaei (2) Yue Zhou (2)

Keywords

distributionally robust optimization (5) structured prediction (4) adversarial learning (4) imitation learning (3) fisher consistency (3) inverse optimal control (3) markov decision process (3) structure learning (2) conditional random field (2) health coaching (2) domain adaptation (2) maximum entropy (2) graphical model (2) risk minimization (2) bipartite matching (2) robust classification (2) support vector machine (2) hinge loss (2) game theory (1) convex optimization (1)

Papers

Imitation Learning via Focused Satisficing IJCAI 2025
Modeling Low-Resource Health Coaching Dialogues via Neuro-Symbolic Goal Summarization and Text-Units-Text Generation COLING 2024
Distributionally Robust Skeleton Learning of Discrete Bayesian Networks NIPS 2023
Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks AISTATS 2022
Moment Distributionally Robust Tree Structured Prediction NIPS 2022
Towards Uniformly Superhuman Autonomy via Subdominance Minimization ICML 2022
Towards Enhancing Health Coaching Dialogue in Low-Resource Settings COLING 2022
Distributionally Robust Imitation Learning NIPS 2021
Adversarial Learning for 3D Matching UAI 2020
Fairness for Robust Log Loss Classification AAAI 2020
Active Learning for Probabilistic Structured Prediction of Cuts and Matchings ICML 2019
Distributionally Robust Graphical Models NIPS 2018
Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes NIPS 2018
Efficient and Consistent Adversarial Bipartite Matching ICML 2018
Adversarial Surrogate Losses for Ordinal Regression NIPS 2017
Adversarial Multiclass Classification: A Risk Minimization Perspective NIPS 2016
Graph-Based Inverse Optimal Control for Robot Manipulation IJCAI 2015
Adversarial Prediction Games for Multivariate Losses NIPS 2015
Softstar: Heuristic-Guided Probabilistic Inference NIPS 2015
Predictive Inverse Optimal Control for Linear-Quadratic-Gaussian Systems AISTATS 2015
Robust Classification Under Sample Selection Bias NIPS 2014