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DSI Webinar

20 Nov

SPS-DSI (DEGAS) Webinar: Vertex, Edge, Clique: What's in a Graph?

Date: 20 November 2024
Time: 2:00 PM (Paris Time)
Presenter(s): Bastian Grossenbacher Rieck

SPS-DSI (DEGAS) Webinar: A Journey Through Graphs for Spatiotemporal Analysis

Date: 9 October 2024
Time: 2:00 PM (Paris Time)
Presenter(s): Jhony H. Giraldo

SPS-DSI (DEGAS) Webinar: Low Distortion Embedding with Bottom-up Manifold Learning

Date: 22 May 2024
Time: 5:00 PM (Paris Time)
Presenter(s): Dr. Gal Mishne

SPS-DSI (DEGAS) Webinar: Edge Varying Graph Neural Networks and Their Stability

Date: 25 April 2024
Time: 3:00 PM (Paris Time)
Presenter(s): Elvin Isufi

SPS-DSI (DEGAS) Webinar: Regularity of Graph Neural Networks

Date: 13 March 2024
Time: 1:00 PM (Paris Time)
Presenter(s): Ron Levie

In many emerging applications, it is of paramount interest to learn hidden parameters from data. For example, self-driving cars may use onboard cameras to identify pedestrians, highway lanes, or traffic signs in various light and weather conditions.

Crowdsourcing has emerged as a powerful paradigm for tackling various machine learning, data mining, and data science tasks, by enlisting inexpensive crowds of human workers, or annotators, to accomplish learning and inference tasks.

Many important application domains generate distributed collections of heterogeneous local datasets. These local datasets are related via an intrinsic network structure that arises from domain-specific notions of similarity between local datasets. Networked federated learning aims at learning a tailored local model for each local dataset. 

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