Andrew D. Lin

dblp:43/2658 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
2since 2021 · last 2026
0000-0003-2111-7307ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 2 · 2 since 2021
YearPublicationVenuePosition
2026 Solving Random Planted CSPs Below the nk/2 Threshold
abstract
We present a family of algorithms to solve random planted instances of any $k$-ary Boolean constraint satisfaction problem (CSP). A randomly planted instance of a Boolean CSP is generated by (1) choosing an arbitrary planted assignment $x^*$, and then (2) sampling constraints from a particular "planting distribution" designed so that $x^*$ will satisfy every constraint. Given an $n$ variable instance of a $k$-ary Boolean CSP with $m$ constraints, our algorithm runs in time $n^{O(\ell)}$ for a choice of a parameter $\ell$, and succeeds in outputting a satisfying assignment if $m \geq O(n) \cdot (n/\ell)^{\frac{k}{2} - 1} \log n$. This generalizes the $\mathrm{poly}(n)$-time algorithm of [FPV15], the case of $\ell = O(1)$, to larger runtimes, and matches the constraint number vs.\ runtime trade-off established for refuting random CSPs by [RRS17]. Our algorithm is conceptually different from the recent algorithm of [GHKM23], which gave a $\mathrm{poly}(n)$-time algorithm to solve semirandom CSPs with $m \geq \tilde{O}(n^{\frac{k}{2}})$ constraints by exploiting conditions that allow a basic SDP to recover the planted assignment $x^*$ exactly. Instead, we forego certificates of uniqueness and recover $x^*$ in two steps: we first use a degree-$O(\ell)$ Sum-of-Squares SDP to find some $\hat{x}$ that is $o(1)$-close to $x^*$, and then we use a second rounding procedure to recover $x^*$ from $\hat{x}$.
Arpon Basu, Jun-Ting Hsieh, Andrew D. Lin, Peter Manohar
ICALP3
2025 Improved Lower Bounds for all Odd-Query Locally Decodable Codes
abstract
We prove that for every odd q ⩾ 3, any q-query binary, possibly non-linear locally decodable code (q-LDC) E : {±1}k→ {±1}nmust satisfy k ⩽ Õ(n1−2/q). For even q, this bound was established in a sequence of works [KT00], [GKST06], [KW04]. For q = 3, the above bound was achieved in a recent work [AGKM23] using an argument that crucially exploits known exponential lower bounds for 2-LDCs. Their strategy hits an inherent bottleneck for q ⩾ 5.Our key insight is identifying a general sufficient condition on the hypergraph of local decoding sets called t-approximate strong regularity. This condition demands that 1) the number of hyperedges containing any given subset of vertices of size t (i.e., its co-degree) be equal to the same but arbitrary value dtup to a multiplicative constant slack, and 2) all other co-degrees be upper-bounded relative to dt. This condition significantly generalizes related proposals in prior works [GKM22], [HKM23], [AGKM23], [HKM+24] that demand absolute upper bounds on all co-degrees.We give an argument based on spectral bounds on Kikuchi Matrices that lower bounds the blocklength of any LDC whose local decoding sets satisfy t-approximate strong regularity for any t ⩽ q. Crucially, unlike prior works, our argument works despite having no non-trivial absolute upper bound on the co-degrees of any set of vertices. To apply our argument to arbitrary q-LDCs, we give a new, greedy, approximate strong regularity decomposition that shows that arbitrary, dense enough hypergraphs can be partitioned (up to a small error) into approximately strongly regular pieces satisfying the required relative bounds on the co-degrees.
Arpon Basu, Jun-Ting Hsieh, Pravesh Kothari, Andrew D. Lin
FOCS4