5,337 research outputs found

    Randomized Query Complexity of Sabotaged and Composed Functions

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    We study the composition question for bounded-error randomized query complexity: Is R(f circ g) = Omega(R(f)R(g))? We show that inserting a simple function h, whose query complexity is onlyTheta(log R(g)), in between f and g allows us to prove R(f circ h circ g) = Omega(R(f)R(h)R(g)). We prove this using a new lower bound measure for randomized query complexity we call randomized sabotage complexity, RS(f). Randomized sabotage complexity has several desirable properties, such as a perfect composition theorem, RS(f circ g) >= RS(f) RS(g), and a composition theorem with randomized query complexity, R(f circ g) = Omega(R(f) RS(g)). It is also a quadratically tight lower bound for total functions and can be quadratically superior to the partition bound, the best known general lower bound for randomized query complexity. Using this technique we also show implications for lifting theorems in communication complexity. We show that a general lifting theorem from zero-error randomized query to communication complexity implies a similar result for bounded-error algorithms for all total functions

    A Composition Theorem for Randomized Query Complexity

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    Let the randomized query complexity of a relation for error probability epsilon be denoted by R_epsilon(). We prove that for any relation f contained in {0,1}^n times R and Boolean function g:{0,1}^m -> {0,1}, R_{1/3}(f o g^n) = Omega(R_{4/9}(f).R_{1/2-1/n^4}(g)), where f o g^n is the relation obtained by composing f and g. We also show using an XOR lemma that R_{1/3}(f o (g^{xor}_{O(log n)})^n) = Omega(log n . R_{4/9}(f) . R_{1/3}(g))$, where g^{xor}_{O(log n)} is the function obtained by composing the XOR function on O(log n) bits and g

    A Composition Theorem for Randomized Query Complexity via Max-Conflict Complexity

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    For any relation f subseteq {0,1}^n x S and any partial Boolean function g:{0,1}^m -> {0,1,*}, we show that R_{1/3}(f o g^n) in Omega(R_{4/9}(f) * sqrt{R_{1/3}(g)})where R_epsilon(*) stands for the bounded-error randomized query complexity with error at most epsilon, and f o g^n subseteq ({0,1}^m)^n x S denotes the composition of f with n instances of g. The new composition theorem is optimal, at least, for the general case of relational problems: A relation f_0 and a partial Boolean function g_0 are constructed, such that R_{4/9}(f_0) in Theta(sqrt n), R_{1/3}(g_0)in Theta(n) and R_{1/3}(f_0 o g_0^n) in Theta(n). The theorem is proved via introducing a new complexity measure, max-conflict complexity, denoted by bar{chi}(*). Its investigation shows that bar{chi}(g) in Omega(sqrt{R_{1/3}(g)}) for any partial Boolean function g and R_{1/3}(f o g^n) in Omega(R_{4/9}(f) * bar{chi}(g)) for any relation f, which readily implies the composition statement. It is further shown that bar{chi}(g) is always at least as large as the sabotage complexity of g

    A composition theorem for randomized query complexity via max conflict complexity

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    Let Rϵ(⋅)R_\epsilon(\cdot) stand for the bounded-error randomized query complexity with error ϵ>0\epsilon > 0. For any relation f⊆{0,1}n×Sf \subseteq \{0,1\}^n \times S and partial Boolean function g⊆{0,1}m×{0,1}g \subseteq \{0,1\}^m \times \{0,1\}, we show that R1/3(f∘gn)∈Ω(R4/9(f)⋅R1/3(g))R_{1/3}(f \circ g^n) \in \Omega(R_{4/9}(f) \cdot \sqrt{R_{1/3}(g)}), where f∘gn⊆({0,1}m)n×Sf \circ g^n \subseteq (\{0,1\}^m)^n \times S is the composition of ff and gg. We give an example of a relation ff and partial Boolean function gg for which this lower bound is tight. We prove our composition theorem by introducing a new complexity measure, the max conflict complexity χˉ(g)\bar \chi(g) of a partial Boolean function gg. We show χˉ(g)∈Ω(R1/3(g))\bar \chi(g) \in \Omega(\sqrt{R_{1/3}(g)}) for any (partial) function gg and R1/3(f∘gn)∈Ω(R4/9(f)⋅χˉ(g))R_{1/3}(f \circ g^n) \in \Omega(R_{4/9}(f) \cdot \bar \chi(g)); these two bounds imply our composition result. We further show that χˉ(g)\bar \chi(g) is always at least as large as the sabotage complexity of gg, introduced by Ben-David and Kothari
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