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Thomas J. Howard

3 papers hereh-index 210 citations3 works total

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

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.DS2
  • cs.LG1

identity via Semantic Scholar / OpenAlex

activity
20212024
most citedLet them have CAKES: A Cutting-Edge Algorithm for Scalable, Efficient, and Exact Search on Big Data

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

cs.DS2024

Generalized compression and compressive search of large datasets

Morgan E. Prior, Thomas Howard, Emily Light +2

The Big Data explosion has necessitated the development of search algorithms that scale sub-linearly in time and memory. While compression algorithms and search algorithms do exist…

cs.DS2023★ 1 cited

Let them have CAKES: A Cutting-Edge Algorithm for Scalable, Efficient, and Exact Search on Big Data

Morgan E. Prior, Thomas J. Howard, Oliver McLaughlin +3

The ongoing Big Data explosion has created a demand for efficient and scalable algorithms for similarity search. Most recent work has focused on \textit{approximate} k-NN search,…

cs.LG2021

Clustered Hierarchical Anomaly and Outlier Detection Algorithms

Najib Ishaq, Thomas J. Howard, Noah M. Daniels

Anomaly and outlier detection is a long-standing problem in machine learning. In some cases, anomaly detection is easy, such as when data are drawn from well-characterized distribu…

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