no code implementations • 18 May 2022 • Deepak Chaurasiya, Anil Surisetty, Nitish Kumar, Alok Singh, Vikrant Dey, Aakarsh Malhotra, Gaurav Dhama, Ankur Arora
We further create an open-source repository for $14$ embedding-based EA methods and present the analysis for invoking further research motivations in the field of EA.
no code implementations • 28 Jan 2022 • Himanshi Charotia, Abhishek Garg, Gaurav Dhama, Naman Maheshwari
However, an underlying assumption spanning all these techniques is the complete availability of data across all levels of the temporal hierarchy, while this offers mathematical convenience but most of the time low frequency data is partially completed and it is not available while forecasting.
no code implementations • 15 Dec 2021 • Himanshi Charotia, Abhishek Garg, Gaurav Dhama, Naman Maheshwari
In the context of demand forecasting or revenue forecasting, this challenge is further exacerbated by a large number of time series as well as limited historical data points available due to changing business context.
no code implementations • 8 Dec 2021 • Siddharth Vimal, Kanishka Kayathwal, Hardik Wadhwa, Gaurav Dhama
In this study, we primarily focus on utility maximization and explore different reward functions to this end.
no code implementations • 30 Nov 2021 • Avi Chawla, Nidhi Mulay, Vikas Bishnoi, Gaurav Dhama
The inception of modeling contextual information using models such as BERT, ELMo, and Flair has significantly improved representation learning for words.
no code implementations • 30 Nov 2021 • Avi Chawla, Nidhi Mulay, Vikas Bishnoi, Gaurav Dhama, Dr. Anil Kumar Singh
Despite this progress, the NLP community has not witnessed any significant work performing a comparative study on the contextualization power of such architectures.