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concepts/maximum-entropy-projection.md
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---
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title: "Maximum Entropy Projection (最大熵投影)"
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created: 2026-07-10
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updated: 2026-07-10
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type: concept
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tags: ["maximum-entropy", "exponential-family", "information-geometry", "moment-matching"]
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sources: ["Jaynes (1957)", "Csiszar (1975)", "[[gid-sphere-2026|GID (You, 2026)]]"]
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---
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# Maximum Entropy Projection (最大熵投影)
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GID 的核心构造——对每个特征空间 V_L,求解满足 V_L 矩约束的**最大熵密度**。
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## 定义
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设 V_L ⊂ L²₀(M, ν) 是均值为零的连续函数的有限维空间,φ_L: M → R^{q_L} 为其基。对矩向量 m ∈ ri(M_L):
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```
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p_{L,m} = arg max_{p} -∫ p log p dν
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s.t. ∫ p dν = 1, ∫ φ_L p dν = m
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```
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## 指数族形式
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最大熵解具有标准指数族密度:
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```
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p_{L,m}(x) = exp{λ_L(m)ᵀ φ_L(x) - ψ_L(λ_L(m))}
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```
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其中 ψ_L(λ) = log ∫ exp{λᵀ φ_L(x)} dν(x) 是对数配分函数,λ_L(m) 是 ∇ψ_L(λ) = m 的解。
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## 嵌套层次
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```
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V₀ = {0} → p₀ = ν (均匀分布)
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V₁ → p₁ = vMF (1 阶球谐特征)
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V₂ → p₂ = Fisher-Bingham 类型 (2 阶球谐特征)
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V₃ → p₃ = 高阶指数族
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...
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```
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每级投影是前一级的**细化**:嵌套特征空间保证 p_L 保留 p_{L-1} 的所有矩信息。
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## 信息几何解释
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最大熵投影等价于在信息几何意义上将 P 向指数族子流形做 **m-projection**(基于 KL 散度的信息投影)。层级 KL-gap 恒等式源于 Amari 的 Pythagorean 定理和信息几何的层次分解。
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## 参考
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- [[geometric-information-decomposition|GID]]
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- [[entropy-deficit|Entropy Deficit]]
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- [[information-gap|Information Gap]]
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