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researcher

Xiao Zhou

5 papers hereh-index 8509 citations9 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 5 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CL1
same name
  • Xiao Zhou — 15 papers, h 8
  • Xiao Zhou — 13 papers, h 9
  • Xiao Zhou — 11 papers, h 4
  • Xiao Zhou — 9 papers, h 3
  • Xiao Zhou — 8 papers, h 2
  • Xiao Zhou — 7 papers, h 3

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
20212023
most citedBlack-box Prompt Learning for Pre-trained Language Models

30 citations · 59 across the 5 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2023

Probabilistic Bilevel Coreset Selection

Xiao Zhou, Renjie Pi, Weizhong Zhang +2

The goal of coreset selection in supervised learning is to produce a weighted subset of data, so that training only on the subset achieves similar performance as training on the en…

cs.LG2023★ 10 cited

Model Agnostic Sample Reweighting for Out-of-Distribution Learning

Xiao Zhou, Yong Lin, Renjie Pi +4

Distributionally robust optimization (DRO) and invariant risk minimization (IRM) are two popular methods proposed to improve out-of-distribution (OOD) generalization performance of…

cs.LG2021★ 15 cited

Efficient Neural Network Training via Forward and Backward Propagation Sparsification

Xiao Zhou, Weizhong Zhang, Zonghao Chen +2

Sparse training is a natural idea to accelerate the training speed of deep neural networks and save the memory usage, especially since large modern neural networks are significantl…

cs.LG2021★ 4 cited

Effective Sparsification of Neural Networks with Global Sparsity Constraint

Xiao Zhou, Weizhong Zhang, Hang Xu +1

Weight pruning is an effective technique to reduce the model size and inference time for deep neural networks in real-world deployments. However, since magnitudes and relative impo…

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