TY - GEN
T1 - Sketching and embedding are equivalent for norms
AU - Andoni, Alexandr
AU - Krauthgamer, Robert
AU - Razenshteyn, Ilya
PY - 2015/6/14
Y1 - 2015/6/14
N2 - An outstanding open question [51, 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 G (0, 2] also admits an efficient sketching scheme. But is the converse true, i.e., is embedding into l p 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 [51, 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.
AB - An outstanding open question [51, 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 G (0, 2] also admits an efficient sketching scheme. But is the converse true, i.e., is embedding into l p 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 [51, 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.
UR - http://www.scopus.com/inward/record.url?scp=84947720334&partnerID=8YFLogxK
U2 - https://doi.org/10.1145/2746539.2746552
DO - https://doi.org/10.1145/2746539.2746552
M3 - منشور من مؤتمر
T3 - Proceedings of the Annual ACM Symposium on Theory of Computing
SP - 479
EP - 488
BT - STOC 2015 - Proceedings of the 2015 ACM Symposium on Theory of Computing
T2 - 47th Annual ACM Symposium on Theory of Computing, STOC 2015
Y2 - 14 June 2015 through 17 June 2015
ER -