WiM Winter Colloquium 2022

Online Only
Thursday, Feb 17, 2022 at 4:00 PM  - 5:00 PM EST 
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Speaker: Prof. Grace Y. Yi
45 Minute talk followed by Q&A session with the speaker 

Title: Statistical Learning of Noisy Data


Abstract: Thanks to the advancement of modern technology in acquiring data, massive data with diverse features and big volumes are becoming more accessible than ever. The impact of big data is significant. While the abundant volume of data presents great opportunities for researchers to extract useful information for new knowledge gain and sensible decision-making, big data present great challenges. A very important yet sometimes overlooked issue is the quality and provenance of the data. Big data are not automatically useful; big data are often raw and involve considerable noise.
Typically, the challenges presented by noisy data with measurement error, missing observations and high dimensionality are particularly intriguing. Noisy data with these features arise ubiquitously from various fields, including health sciences, epidemiological studies, environmental studies, survey research, economics, and so on. In this talk, I will discuss some issues induced by noisy data and how they may complex statistical inferential procedures.

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Event Details

Speaker: Prof. Grace Y. Yi
45 Minute talk followed by Q&A session with the speaker 

Title: Statistical Learning of Noisy Data


Abstract: Thanks to the advancement of modern technology in acquiring data, massive data with diverse features and big volumes are becoming more accessible than ever. The impact of big data is significant. While the abundant volume of data presents great opportunities for researchers to extract useful information for new knowledge gain and sensible decision-making, big data present great challenges. A very important yet sometimes overlooked issue is the quality and provenance of the data. Big data are not automatically useful; big data are often raw and involve considerable noise.
Typically, the challenges presented by noisy data with measurement error, missing observations and high dimensionality are particularly intriguing. Noisy data with these features arise ubiquitously from various fields, including health sciences, epidemiological studies, environmental studies, survey research, economics, and so on. In this talk, I will discuss some issues induced by noisy data and how they may complex statistical inferential procedures.

Speakers

Grace Y. Yi
University of Western Ontario
Professor of Statistical and Actuarial Sciences

Location

Available Online Only
Instructions will be sent out via email after registration.

Tickets

Type
Price
WiM Winter Colloquium 2022
Free

Organizer Details

Logo - Women in Mathematics

Women in Mathematics

Faculty of Mathematics, Univeristy of Waterloo

WiM webpage: https://uwaterloo.ca/women-in-mathematics/  

 

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