Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Ashwin Vaswani"'
Autor:
Michael F. Chiang, Ashwin Vaswani, Mehak Aggarwal, John Campbell, Jimmy S. Chen, Katharina Hoebel, Praveer Singh, Jayashree Kalpathy-Cramer, Nishanth Thumbavanam Arun, Ken Chang, Vibha Agarwal, Liangqiong Qu, Christopher P. Bridge, Daniel L. Rubin, Sharut Gupta, R. V. Paul Chan, Charles Lu, Mishka Gidwani, Jay M. Patel, Shruti Raghavan
Model brittleness is a key concern when deploying deep learning models in real-world medical settings. A model that has high performance at one dataset may suffer a significant decline in performance when tested at on different datasets. While poolin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3d151dbb0728719c03ee016e117702b
https://doi.org/10.21203/rs.3.rs-1087025/v1
https://doi.org/10.21203/rs.3.rs-1087025/v1
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030863647
ICANN (3)
ICANN (3)
Iterative Knowledge Distillation (IKD) [20] is an iterative variant of Hinton’s knowledge distillation framework for deep neural network compression. IKD has shown promising model compression results for image classification tasks where a large amo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52dc2e001f59ce188f59f9bb4f361ffb
https://doi.org/10.1007/978-3-030-86365-4_44
https://doi.org/10.1007/978-3-030-86365-4_44
Publikováno v:
Communications in Computer and Information Science ISBN: 9783030649111
Sports data has become widely available in the recent past. With the improvement of machine learning techniques, there have been attempts to use sports data to analyze not only the outcome of individual games but also to improve insights and strategi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::11eb530f814347a0a9958107c0efbb9a
https://doi.org/10.1007/978-3-030-64912-8_4
https://doi.org/10.1007/978-3-030-64912-8_4