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A Characterization of Multilabel Learnability.

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Amit Tewari

 

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Efficient bandit algorithms for online multiclass prediction., , и . ICML, том 307 из ACM International Conference Proceeding Series, стр. 440-447. ACM, (2008)An Asymptotically Optimal Algorithm for the One-Dimensional Convex Hull Feasibility Problem., и . CoRR, (2023)Learning in online MDPs: is there a price for handling the communicating case?, и . UAI, том 216 из Proceedings of Machine Learning Research, стр. 293-302. PMLR, (2023)Deterministic MDPs with Adversarial Rewards and Bandit Feedback., , и . UAI, стр. 93-101. AUAI Press, (2012)High-Probability Regret Bounds for Bandit Online Linear Optimization., , , , , и . COLT, стр. 335-342. Omnipress, (2008)Optimality of Fast-Matching Algorithms for Random Networks With Applications to Structural Controllability., , и . IEEE Trans. Control. Netw. Syst., 4 (4): 770-780 (2017)On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization, , и . (2009)Scaling Up Coordinate Descent Algorithms for Large ℓ1 Regularization Problems., , , и . ICML, icml.cc / Omnipress, (2012)Online Multiclass Boosting with Bandit Feedback., , и . CoRR, (2018)Online Multiclass Boosting with Bandit Feedback., , и . AISTATS, том 89 из Proceedings of Machine Learning Research, стр. 1148-1156. PMLR, (2019)