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Wenyu Chen

7 papers here

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

author position
  • first author1
  • middle author5
  • last author1

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

fields
  • cs.LG4
  • cs.CV2
  • math.ST1
ORCID 0009-0007-7952-7735
same name
  • Wenyu Chen — 5 papers
  • Wenyu Chen — 5 papers
  • Wenyu Chen — 2 papers
  • Wenyu Chen — 2 papers
  • Wenyu Chen — 1 paper, h 4
  • Wenyu Chen — 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
20162025
most citedTrimmed Conformal Prediction for High-Dimensional Models

8 citations · 15 across the 7 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2024★ 1 cited

FALCON: FLOP-Aware Combinatorial Optimization for Neural Network Pruning

Xiang Meng, Wenyu Chen, Riade Benbaki +1

The increasing computational demands of modern neural networks present deployment challenges on resource-constrained devices. Network pruning offers a solution to reduce model size…

cs.LG2024★ 1 cited

Robust Graph Structure Learning under Heterophily

Xuanting Xie, Zhao Kang, Wenyu Chen

Graph is a fundamental mathematical structure in characterizing relations between different objects and has been widely used on various learning tasks. Most methods implicitly assu…

cs.LG2023★ 2 cited

COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search

Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh +3

The sparse Mixture-of-Experts (Sparse-MoE) framework efficiently scales up model capacity in various domains, such as natural language processing and vision. Sparse-MoEs select a s…

cs.LG2023★ 3 cited

Fast as CHITA: Neural Network Pruning with Combinatorial Optimization

Riade Benbaki, Wenyu Chen, Xiang Meng +4

The sheer size of modern neural networks makes model serving a serious computational challenge. A popular class of compression techniques overcomes this challenge by pruning or spa…

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