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- W2010511039 abstract "In the kernel clustering problem we are given a (large) n x n symmetric positive semidefinite matrix A = (aij) with Σni=1 Σnj=1aij = 0 and a (small) k x k symmetric positive semidefinite matrix B = (bij). The goal is to find a partition {S1, ..., Sk} of {1, ... n} which maximizes Σki=1 Σkj=1 (Σ(p, q)e Si x Sj apq) bij. We design a polynomial time approximation algorithm that achieves an approximation ratio of R(B)2/C(B), where R(B) and C(B) are geometric parameters that depend only on the matrix B, defined as follows: if bij = 0, achieving an approximation guarantee of (1 - e)R(B)2/C(B) is Unique Games hard." @default.
- W2010511039 created "2016-06-24" @default.
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- W2010511039 date "2010-01-17" @default.
- W2010511039 modified "2023-09-27" @default.
- W2010511039 title "Sharp kernel clustering algorithms and their associated Grothendieck inequalities" @default.
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- W2010511039 doi "https://doi.org/10.5555/1873601.1873656" @default.
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