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Thomas J. Ashby

4 papers hereh-index 468 citations14 works total

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

author position
  • middle author1
  • last author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.AR1

identity via Semantic Scholar / OpenAlex

activity
20192022
most citedGuidelines for enhancing data locality in selected machine learning algorithms

3 citations · 5 across the 2 of their papers we have counts for

collaborators
Showing 2019 · cs.LGShow all

2 papers · 2 filters

cs.LG2019

Reviewing Data Access Patterns and Computational Redundancy for Machine Learning Algorithms

Imen Chakroun, Tom Vander Aa, Tom Ashby

Machine learning (ML) is probably the first and foremost used technique to deal with the size and complexity of the new generation of data. In this paper, we analyze one of the mea…

cs.LG2019

SMURFF: a High-Performance Framework for Matrix Factorization

Tom Vander Aa, Imen Chakroun, Thomas J. Ashby +10

Bayesian Matrix Factorization (BMF) is a powerful technique for recommender systems because it produces good results and is relatively robust against overfitting. Yet BMF is more c…

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