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Characterizing the Representer Theorem.

, , , and . ICML (1), volume 28 of JMLR Workshop and Conference Proceedings, page 570-578. JMLR.org, (2013)

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Learning mixture models with the regularized latent maximum entropy principle., , , and . IEEE Trans. Neural Networks, 15 (4): 903-916 (2004)Efficient exploration for optimizing immediate reward., and . AAAI/IAAI, page 385-392. AAAI Press / The MIT Press, (1999)Learning to Generalize from Sparse and Underspecified Rewards., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 130-140. PMLR, (2019)Logistic Markov Decision Processes., , , , , and . IJCAI, page 2486-2493. ijcai.org, (2017)Generalized Optimal Reverse Prediction., and . AISTATS, volume 22 of JMLR Proceedings, page 1305-1313. JMLR.org, (2012)Semantic n-gram language modeling with the latent maximum entropy principle., , , and . ICASSP (1), page 376-379. IEEE, (2003)Batch Stationary Distribution Estimation., , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 10203-10213. PMLR, (2020)Neural Stochastic Dual Dynamic Programming., , , , and . ICLR, OpenReview.net, (2022)Characterizing the Gap Between Actor-Critic and Policy Gradient., , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 11101-11111. PMLR, (2021)Revisiting Sampling for Combinatorial Optimization., , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 32859-32874. PMLR, (2023)