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Quanquan Gu

4 papers here

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

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • stat.ML1
ORCID 0000-0001-9830-793X
same name
  • Quanquan Gu — 129 papers, h 64
  • Quanquan Gu — 15 papers, h 10
  • Quanquan Gu — 12 papers, h 9
  • Quanquan Gu — 12 papers, h 10
  • Quanquan Gu — 11 papers, h 2
  • Quanquan Gu — 11 papers, h 6

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
20152025
most citedClosing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks

86 citations · 92 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2025

Higher-order Linear Attention

Yifan Zhang, Zhen Qin, Mengdi Wang +1

The quadratic cost of scaled dot-product attention is a central obstacle to scaling autoregressive language models to long contexts. Linear-time attention and State Space Models (S…

cs.LG2018★ 3 cited

A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks

Jinghui Chen, Dongruo Zhou, Jinfeng Yi +1

Depending on how much information an adversary can access to, adversarial attacks can be classified as white-box attack and black-box attack. For white-box attack, optimization-bas…

cs.LG2018★ 86 cited

Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks

Jinghui Chen, Dongruo Zhou, Yiqi Tang +3

Adaptive gradient methods, which adopt historical gradient information to automatically adjust the learning rate, despite the nice property of fast convergence, have been observed…

stat.ML2015★ 3 cited

Statistical Limits of Convex Relaxations

Zhaoran Wang, Quanquan Gu, Han Liu

Many high dimensional sparse learning problems are formulated as nonconvex optimization. A popular approach to solve these nonconvex optimization problems is through convex relaxat…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.