Oct 13, 2017 · We study planted problems---finding hidden structures in random noisy inputs---through the lens of the sum-of-squares semidefinite programming hierarchy (SoS).
Sep 10, 2019 · We study planted problems—finding hidden structures in random noisy inputs—through the lens of the sum-of-squares semidefinite programming ...
[PDF] The Power of Sum-of-Squares for Detecting Hidden Structures
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Abstract—We study planted problems—finding hid- den structures in random noisy inputs—through the lens of the sum-of-squares semidefinite programming.
Fast spectral algorithms from sum-of-squares proofs: tensor decomposition and planted sparse vectors · Computer Science, Mathematics. STOC · 2016.
We study planted problems-finding hidden structures in random noisy inputs-through the lens of the sum-of-squares semidefinite programming hierarchy (SoS).
Oct 13, 2017 · We study planted problems—finding hidden structures in random noisy inputs—through the lens of the sum-of-squares semidefinite programming ...
Aug 13, 2018 · Bibliographic details on The power of sum-of-squares for detecting hidden structures.
Power of Sum-of-Squares for Detecting Hidden Structures. FOCS 2017. A. Potechin, D. Steurer. Exact Tensor Completion with Sum of Squares. COLT 2017. A ...
This seminar course will introduce and explore Sum-of-Squares (SoS) algorithms in the context of statistics.
The sum of squares hierarchy (SoS) is a model of computation which has the following nice properties: SoS is broadly applicable. SoS is surprisingly powerful.