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pro vyhledávání: '"Beal, Josh"'
Large-scale pretraining of visual representations has led to state-of-the-art performance on a range of benchmark computer vision tasks, yet the benefits of these techniques at extreme scale in complex production systems has been relatively unexplore
Externí odkaz:
http://arxiv.org/abs/2108.05887
Transformers have become the dominant model in natural language processing, owing to their ability to pretrain on massive amounts of data, then transfer to smaller, more specific tasks via fine-tuning. The Vision Transformer was the first major attem
Externí odkaz:
http://arxiv.org/abs/2012.09958
Putting together an ideal outfit is a process that involves creativity and style intuition. This makes it a particularly difficult task to automate. Existing styling products generally involve human specialists and a highly curated set of fashion ite
Externí odkaz:
http://arxiv.org/abs/2006.10792
Homomorphic encryption enables arbitrary computation over data while it remains encrypted. This privacy-preserving feature is attractive for machine learning, but requires significant computational time due to the large overhead of the encryption sch
Externí odkaz:
http://arxiv.org/abs/1811.09953
We introduce an end-to-end private deep learning framework, applied to the task of predicting 30-day readmission from electronic health records. By using differential privacy during training and homomorphic encryption during inference, we demonstrate
Externí odkaz:
http://arxiv.org/abs/1811.09951
Publikováno v:
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Large-scale pretraining of visual representations has led to state-of-the-art performance on a range of benchmark computer vision tasks, yet the benefits of these techniques at extreme scale in complex production systems has been relatively unexplore
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6c59c8e85d73f6df6c217ef23d802bdf
https://doi.org/10.1109/wacv51458.2022.00150
https://doi.org/10.1109/wacv51458.2022.00150
Akademický článek
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Autor:
Beal, Joshua M.
This dissertation investigates the nature of the 2-D mimicking or matching problem, where the objective is to show the existence of a stochastic process Y that has the same joint (2-D) distributions as a given stochastic process X. Typically, the goa
Externí odkaz:
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1367500889
Autor:
Shrieves, Tammy, Hogan, Richard, Middleton, Renée A., Gladys, W., Patton, David H., Childs, Joyice, Beal, Josh
Publikováno v:
Athens News. 3/11/2013, p6-6. 1p.