Li, C., & Czarnecki, K. (2019). Rethinking Expected Cumulative Reward Formalism of Reinforcement Learning: A Micro-Objective Perspective Presented at the Rethinking Expected Cumulative Reward Formalism of Reinforcement Learning: A Micro-Objective Perspective conference. Montreal.
References
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2019
Hurl, B. (2019). Local and Cooperative Autonomous Vehicle Perception from Synthetic Datasets Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/15118 (Original work published 2019)
Sarkar, A., & Czarnecki, K. (2019). A behavior driven approach for sampling rare event situations for autonomous vehicles Presented at the A Behavior Driven Approach for Sampling Rare Event Situations for Autonomous Vehicles conference. Retrieved from https://ieeexplore.ieee.org/abstract/document/8967715
Balasubramanian, V. (2019). 3D Online Multi-Object Tracking for Autonomous Driving Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/14994 (Original work published 2019)
Angus, M. (2019). Towards Pixel-Level OOD Detection for Semantic Segmentation Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/15004 (Original work published 2019)
Li, C., & Czarnecki, K. (2019). Urban Driving with Multi-Objective Deep Reinforcement Learning Presented at the Urban Driving With Multi-Objective Deep Reinforcement Learning conference. Montreal: IFAAMAS.
Deng, J. (2019). MLOD: A multi-view 3D object detection based on robust feature fusion method Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/15086 (Original work published 2019)
Queiroz, R., Berger, T., & Czarnecki, K. (2019). GeoScenario: An Open DSL for Autonomous Driving Scenario Representation Presented at the GeoScenario: An Open DSL for Autonomous Driving Scenario Representation conference. Paris: IEEE.
Babaee, R., Ganesh, V., & Sedwards, S. (2019). Accelerated Learning of Predictive Runtime Monitors for Rare Failure Porto, Portugal: Springer.
Li, C. (2019). Autonomous Driving: A Multi-Objective Deep Reinforcement Learning Approach Waterloo. Retrieved from https://uwspace.uwaterloo.ca/handle/10012/14697 (Original work published 2019)