Approximating Constraint Satisfaction Problems on High-Dimensional Expanders

by   Vedat Levi Alev, et al.

We consider the problem of approximately solving constraint satisfaction problems with arity k > 2 (k-CSPs) on instances satisfying certain expansion properties, when viewed as hypergraphs. Random instances of k-CSPs, which are also highly expanding, are well-known to be hard to approximate using known algorithmic techniques (and are widely believed to be hard to approximate in polynomial time). However, we show that this is not necessarily the case for instances where the hypergraph is a high-dimensional expander. We consider the spectral definition of high-dimensional expansion used by Dinur and Kaufman [FOCS 2017] to construct certain primitives related to PCPs. They measure the expansion in terms of a parameter γ which is the analogue of the second singular value for expanding graphs. Extending the results by Barak, Raghavendra and Steurer [FOCS 2011] for 2-CSPs, we show that if an instance of MAX k-CSP over alphabet [q] is a high-dimensional expander with parameter γ, then it is possible to approximate the maximum fraction of satisfiable constraints up to an additive error ϵ using q^O(k)· (k/ϵ)^O(1) levels of the sum-of-squares SDP hierarchy, provided γ≤ϵ^O(1)· (1/(kq))^O(k). Based on our analysis, we also suggest a notion of threshold-rank for hypergraphs, which can be used to extend the results for approximating 2-CSPs on low threshold-rank graphs. We show that if an instance of MAX k-CSP has threshold rank r for a threshold τ = (ϵ/k)^O(1)· (1/q)^O(k), then it is possible to approximately solve the instance up to additive error ϵ, using r · q^O(k)· (k/ϵ)^O(1) levels of the sum-of-squares hierarchy. As in the case of graphs, high-dimensional expanders (with sufficiently small γ) have threshold rank 1 according to our definition.



There are no comments yet.


page 1

page 2

page 3

page 4


Explicit SoS lower bounds from high-dimensional expanders

We construct an explicit family of 3XOR instances which is hard for O(√(...

Explicit Lower Bounds Against Ω(n)-Rounds of Sum-of-Squares

We construct an explicit family of 3-XOR instances hard for Ω(n)-levels ...

Playing Unique Games on Certified Small-Set Expanders

We give an algorithm for solving unique games (UG) instances whose const...

List Decoding of Direct Sum Codes

We consider families of codes obtained by "lifting" a base code 𝒞 throug...

Bounds on approximating Max kXOR with quantum and classical local algorithms

We consider the power of local algorithms for approximately solving Max ...

Additive Approximations in High Dimensional Nonparametric Regression via the SALSA

High dimensional nonparametric regression is an inherently difficult pro...

Algorithms and Certificates for Boolean CSP Refutation: "Smoothed is no harder than Random"

We present an algorithm for strongly refuting smoothed instances of all ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.