Information Content of Big Data
Abstract
Every day, an enormous volume of data is generated at an unprecedented rate and modern decision-making feels like swimming in a sea of sensors and drowning in data. One of the primary challenges in current data science research is to identify the most valuable information from a large data set. To this end we have investigated the applications of submodular maximization in fairness, privacy, recommender systems, and time series.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 21, 2021
- Accession Number
- AD1140364
Entities
People
- Amin Karbasi
Organizations
- Yale University