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Andrew Yao

dblp:95/3965 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Graph algorithms and graph theory · 56% Combinatorics and discrete mathematics · 28% Information theory · 8%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Graph algorithms and graph theory
graph algorithms
0.912025
Partial and Exact Recovery of a Random Hypergraph from its Graph Projection · COLT 2025
Combinatorics and discrete mathematics › hypergraph
hypergraph reconstruction
0.912025
Partial and Exact Recovery of a Random Hypergraph from its Graph Projection · COLT 2025
Graph algorithms and graph theory
random graphs
0.912025
Partial and Exact Recovery of a Random Hypergraph from its Graph Projection · COLT 2025
Information theory › signal processing › compressed sensing
exact recovery
0.312025
Partial and Exact Recovery of a Random Hypergraph from its Graph Projection · COLT 2025
Algorithms and data structures › clustering
partial recovery
0.312025
Partial and Exact Recovery of a Random Hypergraph from its Graph Projection · COLT 2025

Methods — techniques the papers use, named apart from their topics

information-theoretic threshold analysis · 0.9
YearPublicationVenuePosition
2025 Partial and Exact Recovery of a Random Hypergraph from its Graph Projection
abstract
Consider a $d$-uniform random hypergraph on $n$ vertices in which hyperedges are included iid so that the average degree is $n^\delta$. The projection of a hypergraph is a graph on the same $n$ vertices where an edge connects two vertices if and only if they belong to some hyperedge. The goal is to reconstruct the hypergraph given its projection. An earlier work of Bresler, Guo, and Polyanskiy (COLT 2024) showed that exact recovery for $d=3$ is possible if and only if $\delta < 2/5$. This work completely resolves the question for all values of $d$ for both exact and partial recovery and for both cases of whether multiplicity information about each edge is available or not. In addition, we show that the reconstruction fidelity undergoes an all-or-nothing transition at a threshold. In particular, this resolves all conjectures from Bresler, Guo, and Polyanskiy (COLT 2024).
Guy Bresler, Chenghao Guo, Yury Polyanskiy, Andrew Yao
COLT4