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Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels., , , , , and . NeurIPS, page 5724-5734. (2019)Optimism in Reinforcement Learning with Generalized Linear Function Approximation., , , and . ICLR, OpenReview.net, (2021)Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 42698-42723. PMLR, (2023)Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels, , , , , and . (2019)Dimensionality Reduction for Tukey Regression., , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 1262-1271. PMLR, (2019)Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?, , , and . (2019)cite arxiv:1910.03016.Exponential separations in the energy complexity of leader election., , , , and . STOC, page 771-783. ACM, (2017)Efficient Near-optimal Algorithms for Barter Exchange., , , and . AAMAS, page 362-370. ACM, (2017)Agnostic Q-learning with Function Approximation in Deterministic Systems: Tight Bounds on Approximation Error and Sample Complexity., , , and . CoRR, (2020)Online Sub-Sampling for Reinforcement Learning with General Function Approximation., , , and . CoRR, (2021)