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Kexin Wang

5 papers hereh-index 319 citations8 works total

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

author position
  • first author3
  • middle author1
  • last author1

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • stat.ML2
  • math.AG1
  • math.NA1
  • math.ST1
same name
  • Kexin Wang — 4 papers, h 6
  • Kexin Wang — 4 papers, h 4
  • Kexin Wang — 3 papers, h 2
  • Kexin Wang — 3 papers, h 0
  • Kexin Wang — 2 papers, h 4
  • Kexin Wang — 2 papers, h 5

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

collaborators

5 papers

stat.ML2026

Tensor-based second-order causal discovery

Nathan Ouyang, Kexin Wang, Anna Seigal

Causal discovery seeks to uncover the causal dependencies among variables. For this purpose, we propose an algorithm called Tensor-based Second-order Causal Discovery (TSCD). Its i…

math.NA2026

Multi-subspace power method for decomposing partially symmetric tensors

Kexin Wang, João M. Pereira, Joe Kileel +1

We present an algorithm for low rank decomposition of tensors of any symmetry type, from fully asymmetric to fully symmetric. It recovers the decomposition one summand at a time vi…

math.AG2026

A Real Generalized Trisecant Trichotomy

Kristian Ranestad, Anna Seigal, Kexin Wang

The classical trisecant lemma says that a general chord of a non-degenerate space curve is not a trisecant; that is, the chord only meets the curve in two points. The generalized t…

math.ST2026

Contrastive independent component analysis

Kexin Wang, Aida Maraj, Anna Seigal

In recent years, there has been growing interest in jointly analyzing a foreground dataset, representing an experimental group, and a background dataset, representing a control gro…

stat.ML2026

Multi-context principal component analysis

Kexin Wang, Salil Bhate, João M. Pereira +3

Principal component analysis (PCA) is a tool to capture factors that explain variation in data. Across domains, data are now collected across multiple contexts (for example, indivi…

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