Reconstruction of Depth-4 Multilinear Circuits

We present a deterministic algorithm for reconstructing multilinear ΣΠΣΠ ( k ) circuits, i.e. multilinear depth-4 circuits with fan-in k at the top + gate. For any fixed k , given black-box access to a polynomial \(f \in \mathbb {F}[x_{1},x_{2},\ldots,x_{n} ] \) computable by a multilinear ΣΠΣΠ ( k ) circuit of size s , the algorithm runs in time quasi-poly( \(n,s,|\mathbb {F}|) \) and outputs a multilinear ΣΠΣΠ ( k ) circuit of size quasi-poly( n , s ) that computes f . Our result solves an open problem posed in [GKL12] (STOC, 2012). Indeed, prior to our work, efficient reconstruction algorithms for multilinear ΣΠΣΠ ( k ) circuits were known only for the case of k = 2 [GKL12,Vol17].

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Publication Details

Journal
ACM Transactions on Computation Theory
Published
2025-03-28
DOI
https://doi.org/10.1145/3726532
Citations
1
Primary Topic
Machine Learning and Algorithms
Type
article
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article

Reconstruction of Depth-4 Multilinear Circuits

Shubhangi Saraf, Vishwas Bhargava, Ilya Volkovich
1 citations
ACM Transactions on Computation Theory
Machine Learning and Algorithms
article

Reconstruction of Depth-4 Multilinear Circuits

Shubhangi Saraf, Vishwas Bhargava, Ilya Volkovich
article en
1 citations

Abstract

We present a deterministic algorithm for reconstructing multilinear ΣΠΣΠ ( k ) circuits, i.e. multilinear depth-4 circuits with fan-in k at the top + gate. For any fixed k , given black-box access to a polynomial \(f \in \mathbb {F}[x_{1},x_{2},\ldots,x_{n} ] \) computable by a multilinear ΣΠΣΠ ( k ) circuit of size s , the algorithm runs in time quasi-poly( \(n,s,|\mathbb {F}|) \) and outputs a multilinear ΣΠΣΠ ( k ) circuit of size quasi-poly( n , s ) that computes f . Our result solves an open problem posed in [GKL12] (STOC, 2012). Indeed, prior to our work, efficient reconstruction algorithms for multilinear ΣΠΣΠ ( k ) circuits were known only for the case of k = 2 [GKL12,Vol17].

ACM Transactions on Computation Theory
Boston College (US), California Institute of Technology (US), University of Toronto (CA)
Openalex Percentile: Top 100%
Machine Learning and Algorithms
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