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researcher

Wei Huang

4 papers here

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

author position
  • first author2
  • middle author2

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

fields
  • cs.LG2
  • cs.CV1
  • cs.IR1
ORCID 0000-0002-4817-8858
same name
  • Wei Huang — 11 papers, h 14
  • Wei Huang — 7 papers
  • Wei Huang — 6 papers
  • Wei Huang — 4 papers
  • Wei Huang — 4 papers, h 20
  • Wei Huang — 3 papers, h 4

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
20192023
most citedImplicit bias of deep linear networks in the large learning rate phase

3 citations · 8 across the 4 of their papers we have counts for

collaborators

4 papers

cs.IR2023★ 3 cited

Rethinking Large-scale Pre-ranking System: Entire-chain Cross-domain Models

Jinbo Song, Ruoran Huang, Xinyang Wang +9

Industrial systems such as recommender systems and online advertising, have been widely equipped with multi-stage architectures, which are divided into several cascaded modules, in…

cs.CV2023

Domain Adaptive Synapse Detection with Weak Point Annotations

Qi Chen, Wei Huang, Yueyi Zhang +1

The development of learning-based methods has greatly improved the detection of synapses from electron microscopy (EM) images. However, training a model for each dataset is time-co…

cs.LG2020★ 3 cited

Implicit bias of deep linear networks in the large learning rate phase

Wei Huang, Weitao Du, Richard Yi Da Xu +1

Most theoretical studies explaining the regularization effect in deep learning have only focused on gradient descent with a sufficient small learning rate or even gradient flow (in…

cs.LG2019★ 2 cited

Gaussian Process Latent Variable Model Factorization for Context-aware Recommender Systems

Wei Huang, Richard Yi Da Xu

Context-aware recommender systems (CARS) have gained increasing attention due to their ability to utilize contextual information. Compared to traditional recommender systems, CARS…

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