Brian Ziebart
22 papers · 2005–2025 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (48) π Academic Marathon Β· Ultra π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π
Keyword Champion
(3)
ποΈ
Keyword Collector
(102)
π
Trend Setter
π
Century Club Β· Bronze
π₯
Unstoppable Β· Silver
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Renaissance Researcher
(6)
Top co-authors
Research topics
Machine Learning
(20)
Learning Types
(14)
Artificial Intelligence
(11)
Core Methods
(10)
Optimization & Theory
(10)
Core AI
(9)
Application Areas
(6)
Mathematics & Optimization
(4)
Reinforcement Learning
(4)
Methods
(4)
Bayesian & Probabilistic
(3)
Optimization
(3)
Deep Learning
(2)
Healthcare & Medicine
(2)
Natural Language Processing
(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
NeurIPS 2023
Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks
AISTATS 2022
Moment Distributionally Robust Tree Structured Prediction
NeurIPS 2022
Towards Enhancing Health Coaching Dialogue in Low-Resource Settings
COLING 2022
Towards Uniformly Superhuman Autonomy via Subdominance Minimization
ICML 2022
Distributionally Robust Imitation Learning
NeurIPS 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
NeurIPS 2018
Efficient and Consistent Adversarial Bipartite Matching
ICML 2018
Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes
NeurIPS 2018
Adversarial Surrogate Losses for Ordinal Regression
NeurIPS 2017
Adversarial Multiclass Classification: A Risk Minimization Perspective
NeurIPS 2016
Adversarial Prediction Games for Multivariate Losses
NeurIPS 2015
Graph-Based Inverse Optimal Control for Robot Manipulation
IJCAI 2015
Predictive Inverse Optimal Control for Linear-Quadratic-Gaussian Systems
AISTATS 2015
Softstar: Heuristic-Guided Probabilistic Inference
NeurIPS 2015
Robust Classification Under Sample Selection Bias
NeurIPS 2014
Inverse Optimal Heuristic Control for Imitation Learning
AISTATS 2005