ACRE: Accelerating Random Forests for Explainability

Author:

McCrabb Andrew1ORCID,Ahmed Aymen2ORCID,Bertacco Valeria2ORCID

Affiliation:

1. University of Michigan, United States

2. University of Michigan, USA

Funder

SRC and DARPA

Publisher

ACM

Reference63 articles.

1. [n. d.]. Adult Census Dataset. https://archive.ics.uci.edu/ml/datasets/adult. [n. d.]. Adult Census Dataset. https://archive.ics.uci.edu/ml/datasets/adult.

2. [n. d.]. English Premier League (EPL) Results. www.kaggle.com/datasets/irkaal/english-premier-league-results. [n. d.]. English Premier League (EPL) Results. www.kaggle.com/datasets/irkaal/english-premier-league-results.

3. S. Aga , N. Jayasena , and M. Ignatowski . 2019. Co-ML: a case for Co llaborative ML acceleration using near-data processing . In Proc. MEMSYS. S. Aga, N. Jayasena, and M. Ignatowski. 2019. Co-ML: a case for Co llaborative ML acceleration using near-data processing. In Proc. MEMSYS.

4. A scalable processing-in-memory accelerator for parallel graph processing

5. F. Alimoglu and E. Alpaydin . 1996. Methods of combining multiple classifiers based on different representations for pen-based handwritten digit recognition . In Proc. TAINN. F. Alimoglu and E. Alpaydin. 1996. Methods of combining multiple classifiers based on different representations for pen-based handwritten digit recognition. In Proc. TAINN.

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