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James M. Murphy

Tufts University

23 papers hereh-index 14566 citations46 works total

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

author position
  • sole author1
  • first author3
  • middle author7
  • last author12

Across the 23 of 23 papers where every author was matched, so the position is known.

fields
  • stat.ML8
  • cs.CV7
  • cs.LG5
  • math.FA2
  • math.SP1
affiliations
  • Tufts University
same name
  • James M. Murphy — 8 papers, h 1
  • James M. Murphy — 3 papers, h 5
  • James M. Murphy — 3 papers, h 1
  • James M. Murphy — 2 papers, h 2
  • James M. Murphy — 1 paper, h 3

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
20162023
most citedPath-Based Spectral Clustering: Guarantees, Robustness to Outliers, and Fast Algorithms

37 citations · 108 across the 15 of their papers we have counts for

collaborators
Showing 2020Show all

3 papers · 1 filter

stat.ML2020

Balancing Geometry and Density: Path Distances on High-Dimensional Data

Anna Little, Daniel McKenzie, James Murphy

New geometric and computational analyses of power-weighted shortest-path distances (PWSPDs) are presented. By illuminating the way these metrics balance density and geometry in the…

cs.CV2020★ 1 cited

Hyperspectral Image Clustering with Spatially-Regularized Ultrametrics

Shukun Zhang, James M. Murphy

We propose a method for the unsupervised clustering of hyperspectral images based on spatially regularized spectral clustering with ultrametric path distances. The proposed method…

stat.ML2020★ 1 cited

Diffusion State Distances: Multitemporal Analysis, Fast Algorithms, and Applications to Biological Networks

Lenore Cowen, Kapil Devkota, Xiaozhe Hu +2

Data-dependent metrics are powerful tools for learning the underlying structure of high-dimensional data. This article develops and analyzes a data-dependent metric known as diffus…

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