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pro vyhledávání: '"Silfa, Franyell"'
Deep Neural Networks (DNNs) are the de facto algorithm for tackling cognitive tasks in real-world applications such as speech recognition and natural language processing. DNN inference comprises numerous dot product operations between inputs and weig
Externí odkaz:
http://arxiv.org/abs/2311.10487
Binary Neural Networks (BNNs) are showing tremendous success on realistic image classification tasks. Notably, their accuracy is similar to the state-of-the-art accuracy obtained by full-precision models tailored to edge devices. In this regard, BNNs
Externí odkaz:
http://arxiv.org/abs/2212.00608
Recurrent Neural Networks (RNNs) are a key technology for applications such as automatic speech recognition or machine translation. Unlike conventional feed-forward DNNs, RNNs remember past information to improve the accuracy of future predictions an
Externí odkaz:
http://arxiv.org/abs/2202.06563
Recurrent Neural Network (RNN) inference exhibits low hardware utilization due to the strict data dependencies across time-steps. Batching multiple requests can increase throughput. However, RNN batching requires a large amount of padding since the b
Externí odkaz:
http://arxiv.org/abs/2009.10656
The use of low numerical precision is a fundamental optimization included in modern accelerators for Deep Neural Networks (DNNs). The number of bits of the numerical representation is set to the minimum precision that is able to retain accuracy based
Externí odkaz:
http://arxiv.org/abs/1911.04244
Publikováno v:
PACT '18 Proceedings of the 27th International Conference on Parallel Architectures and Compilation Techniques, Article No. 18, 2018
Recurrent Neural Networks (RNNs) are a key technology for emerging applications such as automatic speech recognition, machine translation or image description. Long Short Term Memory (LSTM) networks are the most successful RNN implementation, as they
Externí odkaz:
http://arxiv.org/abs/1711.07480
Akademický článek
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Autor:
Silfa, Franyell
Publikováno v:
TDX (Tesis Doctorals en Xarxa)
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
TDR: Tesis Doctorales en Red
CBUC, CESCA
TDR. Tesis Doctorales en Red
instname
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
TDR: Tesis Doctorales en Red
CBUC, CESCA
TDR. Tesis Doctorales en Red
instname
Deep Learning algorithms have been remarkably successful in applications such as Automatic Speech Recognition and Machine Translation. Thus, these kinds of applications are ubiquitous in our lives and are found in a plethora of devices. These algorit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::33c559b21d0807d3384292adc599b114
https://hdl.handle.net/10803/6714482117/344357
https://hdl.handle.net/10803/6714482117/344357
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
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Publikováno v:
IEEE Sensors Journal; May2015, Vol. 16 Issue 10, p3670-3678, 9p
