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Joe Kileel

18 papers hereh-index 10322 citations23 works total

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

author position
  • first author4
  • middle author8
  • last author6

Across the 18 of 18 papers where every author was matched, so the position is known.

fields
  • math.NA5
  • math.AG4
  • cs.CV3
  • cs.LG2
  • math.OC2
  • cs.AI1
same name
  • Joe Kileel — 5 papers, h 4
  • Joe Kileel — 5 papers, h 2
  • Joe Kileel — 3 papers, h 2
  • Joe Kileel — 2 papers, h 2
  • Joe Kileel — 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
20162026
most citedOn the Expressive Power of Deep Polynomial Neural Networks

34 citations · 65 across the 16 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

math.NA2022

Moment Estimation for Nonparametric Mixture Models Through Implicit Tensor Decomposition

Yifan Zhang, Joe Kileel

We present an alternating least squares type numerical optimization scheme to estimate conditionally-independent mixture models in Rn, without parameterizing the distri…

math.AG2022★ 1 cited

Snapshot of Algebraic Vision

Joe Kileel, Kathlén Kohn

In this survey article, we present interactions between algebraic geometry and computer vision, which have recently come under the header of algebraic vision. The subject has given…

math.NA2022

Scalable symmetric Tucker tensor decomposition

Ruhui Jin, Joe Kileel, Tamara G. Kolda +1

We study the best low-rank Tucker decomposition of symmetric tensors. The motivating application is decomposing higher-order multivariate moments. Moment tensors have special struc…

stat.ML2022★ 4 cited

Tensor Moments of Gaussian Mixture Models: Theory and Applications

João M. Pereira, Joe Kileel, Tamara G. Kolda

Gaussian mixture models (GMMs) are fundamental tools in statistical and data sciences. We study the moments of multivariate Gaussians and GMMs. The d-th moment of an n-dimensio…

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