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researcher

W. Cao

14 papers hereh-index 161.6k citations32 works total

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

author position
  • middle author13

Across the 13 of 14 papers where every author was matched, so the position is known.

fields
  • cs.LG9
  • cs.CL1
  • physics.ao-ph1
  • q-bio.PE1
  • q-fin.ST1
  • stat.ME1
same name
  • W. Cao — 55 papers, h 29
  • W. Cao — 33 papers, h 12
  • W. Cao — 22 papers, h 12
  • W. Cao — 21 papers, h 13
  • W. Cao — 17 papers, h 9
  • W. Cao — 13 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 citedSelf-paced Ensemble for Highly Imbalanced Massive Data Classification

169 citations · 369 across the 14 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

physics.ao-ph2023★ 1 cited

Near-real-time monitoring of global ocean carbon sink

Piyu Ke, Xiaofan Gui, Wei Cao +11

Mitigation of climate change will highly rely on a carbon emission trajectory that achieves carbon neutrality by the 2050s. The ocean plays a critical role in modulating climate ch…

cs.LG2023

NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time-Series Pretraining

Chenguo Lin, Xumeng Wen, Wei Cao +4

Recent research on time-series self-supervised models shows great promise in learning semantic representations. However, it has been limited to small-scale datasets, e.g., thousand…

cs.LG2023★ 42 cited

Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series

Jiawen Zhang, Shun Zheng, Wei Cao +2

Irregularly sampled multivariate time series are ubiquitous in various fields, particularly in healthcare, and exhibit two key characteristics: intra-series irregularity and inter-…

cs.LG2023

UADB: Unsupervised Anomaly Detection Booster

Hangting Ye, Zhining Liu, Xinyi Shen +6

Unsupervised Anomaly Detection (UAD) is a key data mining problem owing to its wide real-world applications. Due to the complete absence of supervision signals, UAD methods rely on…

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