Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Shrey Shrivastava"'
Autor:
Phanwadee Sinthong, Dhaval Patel, Nianjun Zhou, Shrey Shrivastava, Arun Iyengar, Anuradha Bhamidipaty
Publikováno v:
Proceedings of the VLDB Endowment. 15:949-957
Data quality assessment is an essential process of any data analysis process including machine learning. The process is time-consuming as it involves multiple independent data quality checks that are performed iteratively at scale on evolving data re
Publikováno v:
IEEE BigData
Data Quality (DQ) has been one of the key focuses as Data Analytics and Artificial Intelligence (AI) fields continue to grow. Yet, data quality analysis has mostly been a disjointed, ad-hoc, and cumbersome process in the overall data analysis workflo
Publikováno v:
IEEE BigData
This paper proposes a verifiable imputation process and an enabling tool for univariate time series. Common ad-hoc and case-specific imputation are not enough to ensure high quality and effective imputation. We adopt the similar verification logic of
Autor:
Jayant R. Kalagnanam, Nianjun Zhou, Syed Yousaf Shah, Shrey Shrivastava, Dhaval Patel, Arun Iyengar, Anuradha Bhamidipaty
Publikováno v:
IEEE BigData
Time series value forecasting using machine learning models utilizing time series features has recently got good attention of Time series analytics community. This paper proposes an automated feature learning mechanisms to filter out most useful feat
Autor:
Wesley M. Gifford, Stuart A. Siegel, Jayant R. Kalagnanam, Chandra Reddy, Shrey Shrivastava, Dhaval Patel
Publikováno v:
IEEE BigData
In this paper, we describe an overarching ML system with a simple programming interface that leverages existing AI and ML frameworks to make the task of model exploration easier. The proposed system introduces a new programming construct namely pipel
Publikováno v:
CogMI
Data quality is critically important for big data and machine learning applications. Data quality systems can analyze data sets for quality and detection of potential errors. They can also provide remediation to fix problems encountered in analyzing
Autor:
A. K. Jha, Anand Jhunjhunwala, Debashish Chakravarty, Siddhant Agarwal, Ashutosh Kumar Singh, Apoorve Singhal, Shubham Sahoo, Yash Khandelwal, Deepank Agrawal, Vibhakar Mohta, R. A. Singh, Vaibhav Lodhi, Shreyas Kowshik, Ritwik Mallik, Adarsh Patnaik, Jaydeep Godbole, Manthan Patel, Shruti Priya, Sombit Dey, Kousshik Raj, Shrey Shrivastava
Publikováno v:
Proceedings of the 2019 2nd International Conference on Control and Robot Technology.
Autonomous vehicles are bound to take over the urban road scenario in the near future. While fully autonomous driving is yet to be deployed on urban roads unconditionally, constrained environments provide an opportunity for preliminary testing and va
Autor:
Wesley M. Gifford, Anuradha Bhamidipaty, Venkata Sitaramagiridharganesh Ganapavarapu, Stuart A. Siegel, Jayant R. Kalagnanam, Dhaval Patel, Shrey Shrivastava
Publikováno v:
IEEE BigData
Fueled with growth in the fields of Internet of Things (IoT) and Big Data, data has become one of the most valuable assets in today’s world. While we are leveraging this data for analyzing complex systems using machine learning and deep learning, a
Autor:
Apoorve Singhal, Shrey Shrivastava, Shreyas Kowshik, Siddhant Agarwal, Vibhakar Mohta, Yash Khandelwal, A. K. Jha, Deepank Agrawal, Vaibhav Lodhi, Debashish Chakravarty
Publikováno v:
2019 International Conference on Image and Video Processing, and Artificial Intelligence.
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030234980
ICWS
ICWS
AI, machine learning, and deep learning tools have now become easily accessible on the cloud. However, the adoption of these cloud-based services for heavy industries has been limited due to the gap between general purpose AI tools and operational re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f81b2f11830dcea7a9429bf266e14ee
https://doi.org/10.1007/978-3-030-23499-7_11
https://doi.org/10.1007/978-3-030-23499-7_11