Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Swarnim Narayan"'
Publikováno v:
IEEE BigData
Reinforcement Learning has yielded promising results for Neural Architecture Search (NAS). In this paper, we demonstrate how its performance can be improved by using a simplified Transformer block to model the policy network. The simplified Transform
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f93d93bc1c30871f5d729a5ead5bf5a7
https://doi.org/10.1109/bigdata50022.2020.9378236
https://doi.org/10.1109/bigdata50022.2020.9378236
Autor:
Swarnim Narayan, Nitinbalaji Singh, Himanshu Rai, Abhinav Rai, Chepuri Shri Krishna, Gursirat Singh Sodhi, Ashish Gupta, Chandrakant Bharti, Varun Mishra
Publikováno v:
IEEE BigData
We present Ultron-AutoML, an open-source, distributed framework for efficient hyper-parameter optimization (HPO) of ML models. Considering that hyper-parameter optimization is compute intensive and time-consuming, the framework has been designed for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c956ac3c814bcbc0461a4dc12e4a2d39
https://doi.org/10.1109/bigdata50022.2020.9378071
https://doi.org/10.1109/bigdata50022.2020.9378071
Autor:
Subimal Deb, D. Nagendra Prasad, Swarnim Narayan, Hains Francis, Souri Banerjee, Sudarshan Ghonge, Astha Sethi
Publikováno v:
Open Journal of Fluid Dynamics. :295-301
We investigate the effect of curvature of the tip and the convexity of an electrode on the localization of suspended particles under the combined effect of dielectrophoresis and AC electroosmosis through simulations using COMSOL Multiphysics. A syste
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bcb02f1e718289cd8b5c55689de41703
https://doi.org/10.4236/ojfd.2015.54030
https://doi.org/10.4236/ojfd.2015.54030
Publikováno v:
IEEE BigData
In this paper we describe the process of building a churn prediction platform for large-scale subscription based businesses and products. These businesses are constantly innovating on customer retention methods, one of which is to predict which custo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::33db81a4216fe45d982fd6d40fb8c216
https://doi.org/10.1109/bigdata.2015.7363888
https://doi.org/10.1109/bigdata.2015.7363888