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Lagrangian Relaxation for Large-Scale Multi-agent Planning.

, , , , , and . IAT, page 494-501. IEEE Computer Society, (2012)978-1-4673-6057-9.

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Two Manifold Problems with Applications to Nonlinear System Identification., and . ICML, icml.cc / Omnipress, (2012)A New View of Predictive State Methods for Dynamical System Learning., , and . CoRR, (2015)A Reduction from Reinforcement Learning to No-Regret Online Learning., , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 3514-3524. PMLR, (2020)Closing the learning-planning loop with predictive state representations., , and . Int. J. Robotics Res., 30 (7): 954-966 (2011)Understanding and Mitigating Accuracy Disparity in Regression., , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 1866-1876. PMLR, (2021)Deep Generative and Discriminative Domain Adaptation., , , , and . AAMAS, page 2315-2317. International Foundation for Autonomous Agents and Multiagent Systems, (2019)Hilbert Space Embeddings of Predictive State Representations., , and . UAI, AUAI Press, (2013)Recurrent Predictive State Policy Networks., , , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 1954-1963. PMLR, (2018)Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction., , , , and . ICML, volume 70 of Proceedings of Machine Learning Research, page 3309-3318. PMLR, (2017)Conditional Learning of Fair Representations., , , and . ICLR, OpenReview.net, (2020)