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Primal decomposition and online algorithms for flow optimization in wireless DTNs.

, , and . GLOBECOM, page 84-90. IEEE, (2013)

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Learning to Generalize Kinematic Models to Novel Objects., , and . CoRL, volume 100 of Proceedings of Machine Learning Research, page 1289-1299. PMLR, (2019)Learning to Infer Kinematic Hierarchies for Novel Object Instances., , , , and . ICRA, page 8461-8467. IEEE, (2022)Multi-Resolution POMDP Planning for Multi-Object Search in 3D., , , and . IROS, page 2022-2029. IEEE, (2021)Building Plannable Representations with Mixed Reality., , , , , and . IROS, page 11146-11153. IEEE, (2020)Q-functionals for Value-Based Continuous Control., , , , and . AAAI, page 8932-8939. AAAI Press, (2023)Learning Markov State Abstractions for Deep Reinforcement Learning., , , and . NeurIPS, page 8229-8241. (2021)Efficient Black-Box Planning Using Macro-Actions with Focused Effects., , , , , and . IJCAI, page 4024-4031. ijcai.org, (2021)Policy search for multi-robot coordination under uncertainty, , , , , and . International Journal of Robotics Research, 35 (14): 1760--1778 (2016)Planning for decentralized control of multiple robots under uncertainty, , , , , and . IEEE International Conference on Robotics and Automation, page 1241--1248. Seattle, WA, USA, IEEE, (May 2015)Finding Macro-Actions with Disentangled Effects for Efficient Planning with the Goal-Count Heuristic., , , , and . CoRR, (2020)