Sketching and Embedding are Equivalent for Norms

Alexandr Andoni, Robert Krauthgamer, Ilya P. Razenshteyn
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引用次数: 42

Abstract

An outstanding open question (http://sublinear.info, Question #5) asks to characterize metric spaces in which distances can be estimated using efficient sketches. Specifically, we say that a sketching algorithm is efficient if it achieves constant approximation using constant sketch size. A well-known result of Indyk (J. ACM, 2006) implies that a metric that admits a constant-distortion embedding into lp for p∈(0,2] also admits an efficient sketching scheme. But is the converse true, i.e., is embedding into lp the only way to achieve efficient sketching? We address these questions for the important special case of normed spaces, by providing an almost complete characterization of sketching in terms of embeddings. In particular, we prove that a finite-dimensional normed space allows efficient sketches if and only if it embeds (linearly) into l1-ε with constant distortion. We further prove that for norms that are closed under sum-product, efficient sketching is equivalent to embedding into l1 with constant distortion. Examples of such norms include the Earth Mover's Distance (specifically its norm variant, called Kantorovich-Rubinstein norm), and the trace norm (a.k.a. Schatten 1-norm or the nuclear norm). Using known non-embeddability theorems for these norms by Naor and Schechtman (SICOMP, 2007) and by Pisier (Compositio. Math., 1978), we then conclude that these spaces do not admit efficient sketches either, making progress towards answering another open question (http://sublinear.info, Question #7). Finally, we observe that resolving whether "sketching is equivalent to embedding into l1 for general norms" (i.e., without the above restriction) is equivalent to resolving a well-known open problem in Functional Analysis posed by Kwapien in 1969.
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写生和嵌入对于规范是等价的
一个突出的开放问题(http://sublinear.info,问题#5)要求描述度量空间,其中可以使用有效的草图估计距离。具体来说,我们说一个素描算法是有效的,如果它使用恒定的草图大小达到恒定的近似。Indyk (J. ACM, 2006)的一个著名结果表明,对于p∈(0,2),一个允许恒定失真嵌入到lp中的度量也允许一个有效的草图方案。但反过来是否正确,即嵌入到lp中是实现高效素描的唯一方法?我们解决了这些问题的赋范空间的重要的特殊情况下,通过提供一个几乎完整的表征素描的嵌入。特别地,我们证明了有限维赋范空间允许有效的草图当且仅当它以恒定的畸变(线性)嵌入到l1-ε中。我们进一步证明了对于在和积下闭合的范数,有效的草图等价于以恒定失真嵌入l1。这些规范的例子包括地球移动者的距离(特别是它的范数变体,称为Kantorovich-Rubinstein范数)和迹范数(又名Schatten 1范数或核范数)。利用Naor和Schechtman (SICOMP, 2007)和Pisier (comtio . o)提出的这些规范的已知不可嵌入性定理。数学。, 1978),然后我们得出结论,这些空间也不承认有效的草图,朝着回答另一个开放问题(http://sublinear.info,问题#7)取得进展。最后,我们观察到,解决“草图是否等同于一般规范的嵌入l1”(即,没有上述限制)等同于解决Kwapien在1969年提出的功能分析中一个众所周知的开放问题。
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