Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Gary S. W. Goh"'
Publikováno v:
ICPR
Integrated Gradients as an attribution method for deep neural network models offers simple implementability. However, it suffers from noisiness of explanations which affects the ease of interpretability. The SmoothGrad technique is proposed to solve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0dd5fc7b7c9af932a2b3aebcbe62d5ae
Publikováno v:
IEEE BigData
Coordination across a supply chain creates win-win situation for all players in that supply chain; we address the benefits, in terms of forecast accuracy, of reconciling demand forecasts across a supply chain. In Part III of this three-part paper, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::328f8832b648d057869c57767dbe8a93
https://doi.org/10.1109/bigdata.2016.7841053
https://doi.org/10.1109/bigdata.2016.7841053
Publikováno v:
IEEE BigData
Traditional manual design of analytical processes is challenging as it requires a general analyst to have good grasping of numerous algorithms and the interaction effects between each technique and the data across multiple domains. Especially in an i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b45742691a1c0c6b0471be9b1c3db554
https://doi.org/10.1109/bigdata.2016.7841042
https://doi.org/10.1109/bigdata.2016.7841042
Publikováno v:
IEEE BigData
Satellite data is discrete in both space and time; it can be considered as temporal snapshots (time series) of lattice processes. As the raw datasets are often too large to host publicly, processed datasets with a coarse spatial resolution are often
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b22282a405c55fd4dc51d0ab7895fba3
https://doi.org/10.1109/bigdata.2016.7841052
https://doi.org/10.1109/bigdata.2016.7841052
Publikováno v:
IEEE BigData
In a big data enabled environment, manufacturers and distributors may have access to previously unobserved retailer-level demand related information. This additional information can be considered in demand forecasting to produce more accurate forecas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24f541d16f0e996d94608be4c4b6f8e5
https://doi.org/10.1109/bigdata.2015.7363994
https://doi.org/10.1109/bigdata.2015.7363994
Publikováno v:
IEEE BigData
We are interested in forecasting a large collection of FMCG demand time series. As the demand of FMCG exists in a hierarchy (from manufacturers to distributors to retailers), the bottom level of the hierarchy may contain thousands or even millions of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2eac3fab95d39810678ba91d96c6599e
https://doi.org/10.1109/bigdata.2015.7363993
https://doi.org/10.1109/bigdata.2015.7363993