Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Implementation of Supervised Pre-Training Methods for Univariate Time Series Forecasting Subject The topic of the resource Deep Learning; Machine Learning; Pre-training; Time Series Forecasting Description An account of the resource There has been a recent deep learning revolution in Computer Vision and Natural Language Processing. One of the biggest reasons for this has been the availability of large-scale datasets to pre-train on. One can argue that the Time Series domain has been left out of the aforementioned revolution. The lack of large scale pretrained models could be one of the reasons for this.While there have been prior experiments using pre-trained models for time series forecasting, the scale of the dataset has been relatively small. One of the few time series problems with large scale data available for pre-training is the financial domain. Therefore, this paper takes advantage of this and pretrains a ID CNN using a dataset of 728 US Stock Daily Closing Price Data in total, 2,533,901 rows. Then, we fine-tune and evaluate a dataset of the NIFTY 200 stocks' Closing Prices, in total 166,379 rows. Our results show a 32% improvement in RMSE and a 36% improvement in convergence speed when compared to a baseline non pre trained model. 2023 IEEE. Creator An entity primarily responsible for making the resource Khanna V.; Joshua J.; Pramila R.M. Source A related resource from which the described resource is derived 2023 2nd International Conference for Innovation in Technology, INOCON 2023 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/INOCON57975.2023.10101327" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/INOCON57975.2023.10101327</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158004628&amp;doi=10.1109%2FINOCON57975.2023.10101327&amp;partnerID=40&amp;md5=4afe75f47e918cb0daf9c01c4f0fd4f0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158004628&amp;doi=10.1109%2fINOCON57975.2023.10101327&amp;partnerID=40&amp;md5=4afe75f47e918cb0daf9c01c4f0fd4f0</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835032092-3 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Khanna V., Christ (Deemed to Be University)Lavasa, Department of Data Science, Maharashtra, Pune, India; Joshua J., Christ (Deemed to Be University)Lavasa, Department of Data Science, Maharashtra, Pune, India; Pramila R.M., Christ (Deemed to Be University)Lavasa, Department of Data Science, Maharashtra, Pune, India