A poly(d,k)-time algorithm learns mixtures of k heavy-tailed spherical distributions via high-dimensional sparse Fourier transforms without needing mean separation.
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Learning Mixture Models via Efficient High-dimensional Sparse Fourier Transforms
A poly(d,k)-time algorithm learns mixtures of k heavy-tailed spherical distributions via high-dimensional sparse Fourier transforms without needing mean separation.