{"title":"阈值函数的多项式表示及其算法应用","authors":"Josh Alman, Timothy M. Chan, Ryan Williams","doi":"10.1109/FOCS.2016.57","DOIUrl":null,"url":null,"abstract":"We design new polynomials for representing threshold functions in three different regimes: probabilistic polynomials of low degree, which need far less randomness than previous constructions, polynomial threshold functions (PTFs) with \"nice\" threshold behavior and degree almost as low as the probabilistic polynomials, and a new notion of probabilistic PTFs where we combine the above techniques to achieve even lower degree with similar \"nice\" threshold behavior. Utilizing these polynomial constructions, we design faster algorithms for a variety of problems: · Offline Hamming Nearest (and Furthest) Neighbors: Given n red and n blue points in d-dimensional Hamming space for d = c log n, we can find an (exact) nearest (or furthest) blue neighbor for every red point in randomized time n<sup>2-1</sup>/O(√clog<sup>2/3</sup> c) or deterministic time n<sup>2-1/O(c log2 c)</sup>. These improve on a randomized n<sup>2-1/O(c log2 c)</sup> bound by Alman and Williams (FOCS'15), and also lead to faster MAX-SAT algorithms for sparse CNFs. · Offline Approximate Nearest (and Furthest) Neighbors: Given n red and n blue points in d-dimensional ℓ<sub>1</sub> or Euclidean space, we can find a (1+ε)-approximate nearest (or furthest) blue neighbor for each red point in randomized time near dn+n<sup>2-Ω(ε1/3/log(1/ε))</sup>. This improves on an algorithm by Valiant (FOCS'12) with randomized time near dn+n<sup>2-Ω(√ε)</sup>, which in turn improves previous methods based on locality-sensitive hashing. · SAT Algorithms and Lower Bounds for Circuits With Linear Threshold Functions: We give a satisfiability algorithm for AC<sup>0</sup>[m] o LTF LTF circuits with a subquadratic number of LTF gates on the bottom layer, and a subexponential number of gates on the other layers, that runs in deterministic 2<sup>n-n</sup><sup>ε</sup> time. This strictly generalizes a SAT algorithm for ACC<sup>0</sup> oLTF circuits of subexponential size by Williams (STOC'14) and also implies new circuit lower bounds for threshold circuits, improving a recent gate lower bound of Kane and Williams (STOC'16). We also give a randomized 2<sup>n-n</sup><sup>ε</sup>-time SAT algorithm for subexponential-size MAJ o AC<sub>0</sub> oLTF o AC<sub>0</sub> oLTF circuits, where the top MAJ gate and middle LTF gates have O(n<sup>6/5-δ</sup>) fan-in.","PeriodicalId":414001,"journal":{"name":"2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"82","resultStr":"{\"title\":\"Polynomial Representations of Threshold Functions and Algorithmic Applications\",\"authors\":\"Josh Alman, Timothy M. 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These improve on a randomized n<sup>2-1/O(c log2 c)</sup> bound by Alman and Williams (FOCS'15), and also lead to faster MAX-SAT algorithms for sparse CNFs. · Offline Approximate Nearest (and Furthest) Neighbors: Given n red and n blue points in d-dimensional ℓ<sub>1</sub> or Euclidean space, we can find a (1+ε)-approximate nearest (or furthest) blue neighbor for each red point in randomized time near dn+n<sup>2-Ω(ε1/3/log(1/ε))</sup>. This improves on an algorithm by Valiant (FOCS'12) with randomized time near dn+n<sup>2-Ω(√ε)</sup>, which in turn improves previous methods based on locality-sensitive hashing. · SAT Algorithms and Lower Bounds for Circuits With Linear Threshold Functions: We give a satisfiability algorithm for AC<sup>0</sup>[m] o LTF LTF circuits with a subquadratic number of LTF gates on the bottom layer, and a subexponential number of gates on the other layers, that runs in deterministic 2<sup>n-n</sup><sup>ε</sup> time. 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引用次数: 82
摘要
我们设计了新的多项式来表示三种不同的阈值函数:低阶的概率多项式,它比以前的结构需要更少的随机性;具有“良好”阈值行为和程度几乎与概率多项式一样低的多项式阈值函数(ptf);以及一个新的概率ptf概念,我们结合上述技术来实现更低的度和类似的“良好”阈值行为。利用这些多项式结构,我们为各种问题设计了更快的算法:·离线汉明最近(和最远)邻居:给定d维Hamming空间中n个红点和n个蓝点,d = clog n,我们可以在随机时间n2-1/O(√clog2/3 c)或确定性时间n2-1/O(c log2c)内为每个红点找到一个(精确的)最近(或最远)的蓝色邻居。这些改进了由Alman和Williams (FOCS'15)约束的随机n2-1/O(c log2c),并且还导致更快的MAX-SAT算法用于稀疏CNFs。·离线近似最近(和最远)邻居:在d维或欧几里德空间中给定n个红点和n个蓝点,我们可以在dn+n2-Ω(ε1/3/log(1/ε))附近的随机时间内为每个红点找到一个(1+ε)-近似最近(或最远)的蓝邻居。该算法改进了Valiant (FOCS'12)在dn+n2-Ω(√ε)附近随机化时间的算法,进而改进了先前基于位置敏感哈希的方法。·具有线性阈值函数的电路的SAT算法和下界:我们给出了AC0[m] o LTF LTF电路的可满足性算法,其底层具有次二次LTF门数,其他层具有次指数门数,在确定性的2n-nε时间内运行。这严格推广了Williams (STOC'14)针对亚指数大小的ACC0 oLTF电路的SAT算法,并且还暗示了阈值电路的新电路下界,改进了Kane和Williams (STOC'16)最近提出的门下界。我们还给出了一种随机2n-nε时间SAT算法,用于亚指数大小的MAJ o AC0 oLTF o AC0 oLTF电路,其中顶部MAJ门和中间LTF门具有o (n6/5-δ)扇入。
Polynomial Representations of Threshold Functions and Algorithmic Applications
We design new polynomials for representing threshold functions in three different regimes: probabilistic polynomials of low degree, which need far less randomness than previous constructions, polynomial threshold functions (PTFs) with "nice" threshold behavior and degree almost as low as the probabilistic polynomials, and a new notion of probabilistic PTFs where we combine the above techniques to achieve even lower degree with similar "nice" threshold behavior. Utilizing these polynomial constructions, we design faster algorithms for a variety of problems: · Offline Hamming Nearest (and Furthest) Neighbors: Given n red and n blue points in d-dimensional Hamming space for d = c log n, we can find an (exact) nearest (or furthest) blue neighbor for every red point in randomized time n2-1/O(√clog2/3 c) or deterministic time n2-1/O(c log2 c). These improve on a randomized n2-1/O(c log2 c) bound by Alman and Williams (FOCS'15), and also lead to faster MAX-SAT algorithms for sparse CNFs. · Offline Approximate Nearest (and Furthest) Neighbors: Given n red and n blue points in d-dimensional ℓ1 or Euclidean space, we can find a (1+ε)-approximate nearest (or furthest) blue neighbor for each red point in randomized time near dn+n2-Ω(ε1/3/log(1/ε)). This improves on an algorithm by Valiant (FOCS'12) with randomized time near dn+n2-Ω(√ε), which in turn improves previous methods based on locality-sensitive hashing. · SAT Algorithms and Lower Bounds for Circuits With Linear Threshold Functions: We give a satisfiability algorithm for AC0[m] o LTF LTF circuits with a subquadratic number of LTF gates on the bottom layer, and a subexponential number of gates on the other layers, that runs in deterministic 2n-nε time. This strictly generalizes a SAT algorithm for ACC0 oLTF circuits of subexponential size by Williams (STOC'14) and also implies new circuit lower bounds for threshold circuits, improving a recent gate lower bound of Kane and Williams (STOC'16). We also give a randomized 2n-nε-time SAT algorithm for subexponential-size MAJ o AC0 oLTF o AC0 oLTF circuits, where the top MAJ gate and middle LTF gates have O(n6/5-δ) fan-in.