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pro vyhledávání: '"Harma, Simla Burcu"'
Autor:
Harma, Simla Burcu, Chakraborty, Ayan, Kostenok, Elizaveta, Mishin, Danila, Ha, Dongho, Falsafi, Babak, Jaggi, Martin, Liu, Ming, Oh, Yunho, Subramanian, Suvinay, Yazdanbakhsh, Amir
The increasing size of deep neural networks necessitates effective model compression to improve computational efficiency and reduce their memory footprint. Sparsity and quantization are two prominent compression methods that have individually demonst
Externí odkaz:
http://arxiv.org/abs/2405.20935
Autor:
Harma, Simla Burcu, Chakraborty, Ayan, Sperry, Nicholas, Falsafi, Babak, Jaggi, Martin, Oh, Yunho
The unprecedented demand for computing resources to train DNN models has led to a search for minimal numerical encoding. Recent state-of-the-art (SOTA) proposals advocate for multi-level scaled narrow bitwidth numerical formats. In this paper, we sho
Externí odkaz:
http://arxiv.org/abs/2211.10737
The unprecedented growth in DNN model complexity, size, and amount of training data has led to a commensurate increase in demand for computing and a search for minimal encoding. Recent research advocates Hybrid Block Floating Point (HBFP) to minimize
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf600513abf7e78c4423f9eb64b2a8b1
http://arxiv.org/abs/2211.10737
http://arxiv.org/abs/2211.10737
Autor:
Harma, Simla Burcu
Teknoloji çağında yaşıyoruz ve son on yılda Yapay Zeka üzerine en çok çalışılan teknoloji olmuştur. Sayısız alanda uygulaması bulunmakla birlikte, Yapay Sinir Ağları ile Makine Çevirisi (YMÇ) temel araştırma alanlarından birisi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::036ad093f3b7bd16de4c71630637bebe
https://acikbilim.yok.gov.tr/handle/20.500.12812/682363
https://acikbilim.yok.gov.tr/handle/20.500.12812/682363