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Xiaoyu Dong

7 papers hereh-index 340 citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2
  • last author4

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.DS4
  • cs.LG2
  • quant-ph1
same name
  • Xiaoyu Dong — 11 papers, h 12
  • Xiaoyu Dong — 10 papers, h 6
  • Xiaoyu Dong — 5 papers, h 7
  • Xiaoyu Dong — 3 papers, h 2
  • Xiaoyu Dong — 1 paper
  • Xiaoyu Dong — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedOptimal Embedding Dimension for Sparse Subspace Embeddings

6 citations · 6 across the 6 of their papers we have counts for

collaborators
Showing cs.DSShow all

4 papers · 1 filter

cs.DS2026

Well-Conditioned Oblivious Perturbations in Linear Space

Shabarish Chenakkod, Michał Dereziński, Xiaoyu Dong +1

Perturbing a deterministic n-dimensional matrix with small Gaussian noise is a cornerstone of smoothed analysis of algorithms [Spielman and Teng, JACM 2004], as it reduces the co…

cs.DS2025

Optimal Subspace Embeddings: Resolving Nelson-Nguyen Conjecture Up to Sub-Polylogarithmic Factors

Shabarish Chenakkod, Michał Dereziński, Xiaoyu Dong

We give a proof of the conjecture of Nelson and Nguyen [FOCS 2013] on the optimal dimension and sparsity of oblivious subspace embeddings, up to sub-polylogarithmic factors: For an…

cs.DS2024

Optimal Oblivious Subspace Embeddings with Near-optimal Sparsity

Shabarish Chenakkod, Michał Dereziński, Xiaoyu Dong

An oblivious subspace embedding is a random m×n matrix Π such that, for any d-dimensional subspace, with high probability Π preserves the norms of all vectors in that…

cs.DS2023★ 6 cited

Optimal Embedding Dimension for Sparse Subspace Embeddings

Shabarish Chenakkod, Michał Dereziński, Xiaoyu Dong +1

A random m×n matrix S is an oblivious subspace embedding (OSE) with parameters ε>0, δ∈(0,1/3) and d≤m≤n, if for any d-dimensional subspace $W\subseteq R…

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