Khaleelulla Khan

Nov 19, 2024 | arxiv.org | Khaleelulla Khan

May 1, 2024 | arxiv.org | Khaleelulla Khan |Mark Schone |Christian Mayr |Khaleelulla Khan Nazeer

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Jan 9, 2024 | arxiv.org | Khaleelulla Khan

Happy π Day! Pi Day is finally here – and so is Giving Day for arXiv! Donate today to directly support arXiv initiatives and help keep open science open. Infinite decimals. Infinite new ideas to discover. Infinite reasons to give.

Dec 14, 2023 | arxiv.org | Khaleelulla Khan

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Nov 13, 2023 | arxiv.org | Khaleelulla Khan

[Submitted on 13 Nov 2023 (v1), last revised 26 Nov 2024 (this version, v3)] Title:Activity Sparsity Complements Weight Sparsity for Efficient RNN Inference View a PDF of the paper titled Activity Sparsity Complements Weight Sparsity for Efficient RNN Inference, by Rishav Mukherji and 4 other authors View PDF HTML (experimental) Abstract:Artificial neural networks open up unprecedented machine learning capabilities at the cost of ever growing computational requirements.