Brian D Ziebart
Brian D Ziebart
Associate Professor of Computer Science, University of Illinois at Chicago
Geverifieerd e-mailadres voor uic.edu - Homepage
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Maximum Entropy Inverse Reinforcement Learning
BD Ziebart, AL Maas, JA Bagnell, AK Dey
AAAI Conference on Artificial Intelligence, 1433-1438, 2008
Activity forecasting
KM Kitani, BD Ziebart, JA Bagnell, M Hebert
European Conference on Computer Vision (ECCV), 201-214, 2012
Planning-based prediction for pedestrians
BD Ziebart, N Ratliff, G Gallagher, C Mertz, K Peterson, JA Bagnell, ...
International Conference on Intelligent Robots and Systems (IROS), 3931-3936, 2009
Modeling Purposeful Adaptive Behavior with the Principle of Maximum Causal Entropy
BD Ziebart
Carnegie Mellon University, 2010
Navigate like a cabbie: Probabilistic reasoning from observed context-aware behavior
BD Ziebart, AL Maas, AK Dey, JA Bagnell
International Conference on Ubiquitous Computing (Ubicomp), 322-331, 2008
Modeling interaction via the principle of maximum causal entropy
BD Ziebart, JA Bagnell, AK Dey
🥈International Conference on Machine Learning (ICML), 1247-1254, 2010
System, method and device for predicting navigational decision-making behavior
AK Dey, JA Bagnell, BD Ziebart
US Patent 8,478,642, 2013
Robust classification under sample selection bias
A Liu, B Ziebart
💡 Advances in Neural Information Processing Systems (NIPS), 37-45, 2014
Probabilistic pointing target prediction via inverse optimal control
B Ziebart, A Dey, JA Bagnell
🥈International Conference on Intelligent User Interfaces (IUI), 1-10, 2012
TherML: occupancy prediction for thermostat control
C Koehler, BD Ziebart, J Mankoff, AK Dey
Pervasive and Ubiquitous Computing (Ubicomp), 103-112, 2013
Computational rationalization: The inverse equilibrium problem
K Waugh, BD Ziebart, JA Bagnell
🏆 International Conference on Machine Learning., 2011
Towards a pervasive computing benchmark
A Ranganathan, J Al-Muhtadi, J Biehl, B Ziebart, RH Campbell, B Bailey
Pervasive Computing and Communications Workshops, 194-198, 2005
Human Behavior Modeling with Maximum Entropy Inverse Optimal Control
BD Ziebart, AL Maas, JA Bagnell, AK Dey
AAAI Spring Symposium: Human Behavior Modeling, 92-, 2009
The principle of maximum causal entropy for estimating interacting processes
BD Ziebart, JA Bagnell, AK Dey
IEEE Transactions on Information Theory 59 (4), 1966-1980, 2013
Robust covariate shift regression
X Chen, M Monfort, A Liu, BD Ziebart
Artificial Intelligence and Statistics, 1270-1279, 2016
Robust fairness under covariate shift
A Rezaei, A Liu, O Memarrast, BD Ziebart
Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9419-9427, 2021
Intent Prediction and Trajectory Forecasting via Predictive Inverse Linear-Quadratic Regulation
M Monfort, A Liu, BD Ziebart
AAAI Conference on Artificial Intelligence, 2015
Leveraging Machine Learning to Improve Unwanted Resource Filtering
S Bhagavatula, C Dunn, C Kanich, M Gupta, B Ziebart
Workshop on Artificial Intelligent and Security, 95-102, 2014
Both nearest neighbours and long-term affiliates predict individual locations during collective movement in wild baboons
DR Farine, A Strandburg-Peshkin, T Berger-Wolf, B Ziebart, I Brugere, J Li, ...
Scientific reports 6 (1), 27704, 2016
Adversarial Cost-Sensitive Classification
K Asif, W Xing, S Behpour, BD Ziebart
Uncertainty in Artificial Intelligence, 2015
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