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Yaqing Wang

Baidu Research

4 papers hereh-index 12785 citations22 works total

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

author position
  • first author3
  • middle author1

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

fields
  • cs.LG2
  • cs.CL1
  • cs.CV1
affiliations
  • Baidu Research
Homepage
same name
  • Yaqing Wang — 13 papers
  • Yaqing Wang — 1 paper
  • Yaqing Wang — 1 paper
  • Yaqing Wang — 1 paper
  • Yaqing Wang — 1 paper

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
20182022
most citedLow-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization

2 citations · 3 across the 2 of their papers we have counts for

collaborators

4 papers

cs.CL2022★ 1 cited

AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning

Yaqing Wang, Sahaj Agarwal, Subhabrata Mukherjee +4

Standard fine-tuning of large pre-trained language models (PLMs) for downstream tasks requires updating hundreds of millions to billions of parameters, and storing a large copy of…

cs.LG2022★ 2 cited

Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization

Quanming Yao, Yaqing Wang, Bo Han +1

Nonconvex regularization has been popularly used in low-rank matrix learning. However, extending it for low-rank tensor learning is still computationally expensive. To address this…

cs.LG2019

General Convolutional Sparse Coding with Unknown Noise

Yaqing Wang, James T. Kwok, Lionel M. Ni

Convolutional sparse coding (CSC) can learn representative shift-invariant patterns from multiple kinds of data. However, existing CSC methods can only model noises from Gaussian d…

cs.CV2018

Online Convolutional Sparse Coding with Sample-Dependent Dictionary

Yaqing Wang, Quanming Yao, James T. Kwok +1

Convolutional sparse coding (CSC) has been popularly used for the learning of shift-invariant dictionaries in image and signal processing. However, existing methods have limited sc…

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