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English(EN) From Approximation to Emergence: A Theory of Deep Learning

新专著勾勒深度学习理论从近似到涌现的蓝图

作者 PulseAugur 编辑部 · [2 个来源] ·

一本题为《从近似到涌现：深度学习理论》的新专著，提供了一个统一的、面向证明的现代深度学习理论叙述。本书追溯了该领域从近似和泛化等经典概念到过参数化、生成模型、Transformer和涌现等当代主题的演变。它旨在为研究人员和从业者提供一个严谨的深度学习理论图谱，强调其当前的强大之处、不完整性以及日益增长的对学习机制如何从规模、数据、架构和训练中产生的关注。 AI

影响 为理解当前和未来的深度学习进展提供了全面的理论框架。

排序理由 该条目是arXiv预印本，详细介绍了深度学习的新理论框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv stat.ML 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新专著勾勒深度学习理论从近似到涌现的蓝图

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该条目是arXiv预印本，详细介绍了深度学习的新理论框架。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [2]

  1. arXiv stat.ML TIER_1 English(EN) · Zhilin Zhao ·

    从近似到涌现：深度学习理论

    arXiv:2607.01311v1 Announce Type: cross Abstract: Deep learning has outgrown any single mathematical explanation. From Approximation to Emergence develops a unified, proof-oriented account of modern deep learning theory, tracing a path from the classical foundations of approximat…

  2. arXiv stat.ML TIER_1 English(EN) · Zhilin Zhao ·

    从近似到涌现：深度学习理论

    Deep learning has outgrown any single mathematical explanation. From Approximation to Emergence develops a unified, proof-oriented account of modern deep learning theory, tracing a path from the classical foundations of approximation, optimization, and generalization to the conte…

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