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researcher

K. Harris

25 papers hereh-index 152.8k citations47 works total

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

author position
  • sole author2
  • first author7
  • middle author12
  • last author3

Across the 24 of 25 papers where every author was matched, so the position is known.

fields
  • physics.soc-ph8
  • q-bio.NC3
  • stat.ML3
  • cond-mat.dis-nn2
  • math.DS2
  • nlin.CD2
same name
  • K. Harris — 9 papers, h 74
  • K. Harris — 8 papers, h 6
  • K. Harris — 6 papers, h 3
  • K. Harris — 3 papers, h 4
  • K. Harris — 1 paper, h 2
  • K. Harris — 1 paper, h 0

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
20112026
most citedTemporal patterns of happiness and information in a global social network: Hedonometrics and Twitter

833 citations · 1.6k across the 22 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

stat.ML2019★ 7 cited

Deterministic tensor completion with hypergraph expanders

Kameron Decker Harris, Yizhe Zhu

We provide a novel analysis of low-rank tensor completion based on hypergraph expanders. As a proxy for rank, we minimize the max-quasinorm of the tensor, which generalizes the max…

cs.NE2019★ 1 cited

Additive function approximation in the brain

Kameron Decker Harris

Many biological learning systems such as the mushroom body, hippocampus, and cerebellum are built from sparsely connected networks of neurons. For a new understanding of such netwo…

math.DS2019

Centering Data Improves the Dynamic Mode Decomposition

Seth M. Hirsh, Kameron Decker Harris, J. Nathan Kutz +1

Dynamic mode decomposition (DMD) is a data-driven method that models high-dimensional time series as a sum of spatiotemporal modes, where the temporal modes are constrained by line…

stat.ML2019

Time-varying Autoregression with Low Rank Tensors

Kameron Decker Harris, Aleksandr Aravkin, Rajesh Rao +1

We present a windowed technique to learn parsimonious time-varying autoregressive models from multivariate timeseries. This unsupervised method uncovers interpretable spatiotempora…

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