Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers

Oct 25, 2020
Colby Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough

* 10 pages, 8 figures, 3 tables, appendix 

  Access Paper or Ask Questions

Rank and run-time aware compression of NLP Applications

Oct 06, 2020
Urmish Thakker, Jesse Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina

* Published at SustaiNLP@EMNLP 2020. arXiv admin note: text overlap with arXiv:1906.04886 

  Access Paper or Ask Questions

Benchmarking TinyML Systems: Challenges and Direction

Mar 10, 2020
Colby R. Banbury, Vijay Janapa Reddi, Max Lam, William Fu, Amin Fazel, Jeremy Holleman, Xinyuan Huang, Robert Hurtado, David Kanter, Anton Lokhmotov, David Patterson, Danilo Pau, Jae-sun Seo, Jeff Sieracki, Urmish Thakker, Marian Verhelst, Poonam Yadav

* 5 pages, 1 figure, 2 tables 

  Access Paper or Ask Questions

Federated Learning for Resource-Constrained IoT Devices: Panoramas and State-of-the-art

Feb 25, 2020
Ahmed Imteaj, Urmish Thakker, Shiqiang Wang, Jian Li, M. Hadi Amini


  Access Paper or Ask Questions

Compressing Language Models using Doped Kronecker Products

Jan 31, 2020
Urmish Thakker, Paul Whatamough, Matthew Mattina, Jesse Beu

* Presented at On-device Intelligence Workshop at Third Conference on Machine Learning and Systems (MLSys) 2020 
* Link to Workshop - https://mlsys.org/Conferences/2020/Schedule?showEvent=1297 

  Access Paper or Ask Questions

Ternary MobileNets via Per-Layer Hybrid Filter Banks

Nov 04, 2019
Dibakar Gope, Jesse Beu, Urmish Thakker, Matthew Mattina


  Access Paper or Ask Questions

Pushing the limits of RNN Compression

Oct 09, 2019
Urmish Thakker, Igor Fedorov, Jesse Beu, Dibakar Gope, Chu Zhou, Ganesh Dasika, Matthew Mattina

* 5th edition of Workshop on Energy Efficient Machine Learning and Cognitive Computing at NeurIPS 2019 
* 6 pages. arXiv admin note: substantial text overlap with arXiv:1906.02876 

  Access Paper or Ask Questions

Compressing RNNs for IoT devices by 15-38x using Kronecker Products

Jun 18, 2019
Urmish Thakker, Jesse Beu, Dibakar Gope, Chu Zhou, Igor Fedorov, Ganesh Dasika, Matthew Mattina


  Access Paper or Ask Questions

Run-Time Efficient RNN Compression for Inference on Edge Devices

Jun 18, 2019
Urmish Thakker, Jesse Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina

* Published at 4th edition of Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications at International Symposium of Computer Architecture 2019, Phoenix, Arizona (https://www.emc2-workshop.com/isca-19) colocated with ISCA 2019 

  Access Paper or Ask Questions

A Static Analysis-based Cross-Architecture Performance Prediction Using Machine Learning

Jun 18, 2019
Newsha Ardalani, Urmish Thakker, Aws Albarghouthi, Karu Sankaralingam

* Published at 2nd International Workshop on AI-assisted Design for Architecture Phoenix, AZ, June 22, 2019, colocated with ISCA 

  Access Paper or Ask Questions