YoVDO

Dimension Importance Estimation for Dense Information Retrieval - Tutorial 2.1

Offered By: Association for Computing Machinery (ACM) via YouTube

Tags

Information Retrieval Courses Data Mining Courses Machine Learning Courses Search Algorithms Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a focused conference talk on dimension importance estimation for dense information retrieval. Delve into the research presented by authors Guglielmo Faggioli, Nicola Ferro, Raffaele Perego, and Nicola Tonellotto as part of the Dense Retrieval 1 (T2.1) session at SIGIR 2024. Gain insights into advanced techniques and methodologies for improving dense retrieval systems through dimension importance estimation. Learn about the latest developments in this crucial aspect of information retrieval and its potential impact on search efficiency and effectiveness.

Syllabus

SIGIR 2024 T2.1 [fp] Dimension Importance Estimation for Dense Information Retrieval


Taught by

Association for Computing Machinery (ACM)

Related Courses

Introduction to Data Science
University of Washington via Coursera Big Data Analytics in Healthcare
Georgia Institute of Technology via Udacity More Data Mining with Weka
University of Waikato via Independent Mining Massive Datasets
Stanford University via edX Pattern Discovery in Data Mining
University of Illinois at Urbana-Champaign via Coursera