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pro vyhledávání: '"Ghaemmaghami, Benjamin"'
Autor:
Deng, Zihao, Ghaemmaghami, Benjamin, Singh, Ashish Kumar, Cho, Benjamin, Orshansky, Leo, Erez, Mattan, Orshansky, Michael
Modern DNN-based recommendation systems rely on training-derived embeddings of sparse features. Input sparsity makes obtaining high-quality embeddings for rarely-occurring categories harder as their representations are updated infrequently. We demons
Externí odkaz:
http://arxiv.org/abs/2309.15881
Autor:
Ghaemmaghami, Benjamin, Ozdal, Mustafa, Komuravelli, Rakesh, Korchev, Dmitriy, Mudigere, Dheevatsa, Nair, Krishnakumar, Naumov, Maxim
A key characteristic of deep recommendation models is the immense memory requirements of their embedding tables. These embedding tables can often reach hundreds of gigabytes which increases hardware requirements and training cost. A common technique
Externí odkaz:
http://arxiv.org/abs/2203.15837
Autor:
Ghaemmaghami, Benjamin, Deng, Zihao, Cho, Benjamin, Orshansky, Leo, Singh, Ashish Kumar, Erez, Mattan, Orshansky, Michael
Modern recommendation systems rely on real-valued embeddings of categorical features. Increasing the dimension of embedding vectors improves model accuracy but comes at a high cost to model size. We introduce a multi-layer embedding training (MLET) a
Externí odkaz:
http://arxiv.org/abs/2006.05623
Publikováno v:
In Smart Health December 2019 14
Autor:
Anderson, Martha Smith, Bankole, Azziza, Newbold, Temple M., Goins, Hilda, Fyffe, Nykesha, Lofton, Ashley, Ghaemmaghami, Benjamin, Homdee, Nutta, Hayes, James, Hamid, Tamanna, Park, John, Wolfe, Sean, Alam, Ridwan, Lach, John, Smith-Jackson, Tonya L.
Publikováno v:
In Alzheimer's & Dementia: The Journal of the Alzheimer's Association July 2019 15(7) Supplement:P1450-P1451
Autor:
Anderson, Martha Smith, Bankole, Azziza, Newbold, Temple M., Goins, Hilda, Fyffe, Nykesha, Lofton, Ashley, Ghaemmaghami, Benjamin, Homdee, Nutta, Hayes, James, Hamid, Tamanna, Park, John, Wolfe, Sean, Alam, Ridwan, Lach, John, Smith-Jackson, Tonya L.
Publikováno v:
Alzheimer's & Dementia: The Journal of the Alzheimer's Association; Jul2019 7S Part 28, Vol. 15, pP1450-P1451, 2p
Publikováno v:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2019 Jul; Vol. 2019, pp. 6935-6938.