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A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets.

, , , , и . AISTATS, том 130 из Proceedings of Machine Learning Research, стр. 2548-2556. PMLR, (2021)

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Wahyudi David

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Stable Opponent Shaping in Differentiable Games., , , , и . CoRR, (2018)D3C: Reducing the Price of Anarchy in Multi-Agent Learning., , , , , , и . CoRR, (2020)A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets., , , , и . AISTATS, том 130 из Proceedings of Machine Learning Research, стр. 2548-2556. PMLR, (2021)Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games., , , , , и . AAMAS, стр. 538-547. International Foundation for Autonomous Agents and Multiagent Systems, (2020)Minimax Theorem for Latent Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets., , , , и . CoRR, (2020)Learning the Structure of Sum-Product Networks via an SVD-based Algorithm., , и . UAI, стр. 32-41. AUAI Press, (2015)On the information-theoretic structure of distributed measurements. DCM, том 88 из EPTCS, стр. 28-42. (2011)Information, learning and falsification. CoRR, (2011)Re-evaluating Evaluation, , , и . (2018)cite arxiv:1806.02643Comment: NIPS 2018, final version.Estimating integrated information with TMS pulses during wakefulness, sleep, and under anesthesia.. EMBC, стр. 4717-4720. IEEE, (2011)