Andrew Anderson

Orcid: 0000-0002-4357-4739

Affiliations:
  • Trinity College Dublin, Ireland (PhD)


According to our database1, Andrew Anderson authored at least 21 papers between 2016 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2022
Winograd Convolution for Deep Neural Networks: Efficient Point Selection.
ACM Trans. Embed. Comput. Syst., November, 2022

2021
Taxonomy of Saliency Metrics for Channel Pruning.
IEEE Access, 2021

Domino Saliency Metrics: Improving Existing Channel Saliency Metrics with Structural Information.
Proceedings of the AIxIA 2021 - Advances in Artificial Intelligence, 2021

2020
Error Analysis and Improving the Accuracy of Winograd Convolution for Deep Neural Networks.
ACM Trans. Math. Softw., 2020

Bonseyes AI Pipeline - Bringing AI to You: End-to-end integration of data, algorithms, and deployment tools.
ACM Trans. Internet Things, 2020

Composition of Saliency Metrics for Channel Pruning with a Myopic Oracle.
CoRR, 2020

Composition of Saliency Metrics for Pruning with a Myopic Oracle.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

TASO: Time and Space Optimization for Memory-Constrained DNN Inference.
Proceedings of the 32nd IEEE International Symposium on Computer Architecture and High Performance Computing, 2020

High-Performance Low-Memory Lowering: GEMM-based Algorithms for DNN Convolution.
Proceedings of the 32nd IEEE International Symposium on Computer Architecture and High Performance Computing, 2020

2019
A Taxonomy of Channel Pruning Signals in CNNs.
CoRR, 2019

Performance-Oriented Neural Architecture Search.
Proceedings of the 17th International Conference on High Performance Computing & Simulation, 2019

Scalar Arithmetic Multiple Data: Customizable Precision for Deep Neural Networks.
Proceedings of the 26th IEEE Symposium on Computer Arithmetic, 2019

POSTER: Space and Time Optimal DNN Primitive Selection with Integer Linear Programming.
Proceedings of the 28th International Conference on Parallel Architectures and Compilation Techniques, 2019

2018
Scalar Arithmetic Multiple Data: Customizable Precision for Deep Neural Networks.
CoRR, 2018

Improving accuracy of Winograd convolution for DNNs.
CoRR, 2018

Optimal DNN primitive selection with partitioned boolean quadratic programming.
Proceedings of the 2018 International Symposium on Code Generation and Optimization, 2018

2017
Efficient Multibyte Floating Point Data Formats Using Vectorization.
IEEE Trans. Computers, 2017

Low-memory GEMM-based convolution algorithms for deep neural networks.
CoRR, 2017

Parallel Multi Channel convolution using General Matrix Multiplication.
Proceedings of the 28th IEEE International Conference on Application-specific Systems, 2017

2016
Automatic Vectorization of Interleaved Data Revisited.
ACM Trans. Archit. Code Optim., 2016

Vectorization of Multibyte Floating Point Data Formats.
Proceedings of the 2016 International Conference on Parallel Architectures and Compilation, 2016


  Loading...