[MINI] type i / type ii errors

Ekaterina (Kat) Fedorova from MIT EECS joins us to discuss strategic learning in recommender systems—what happens when users collectively coordinate to game recommendation algorithms. Kat's research reveals surprising findings: algorithmic "protest movements" can paradoxically he ...  Show more

Anas Buhayh discusses multi-stakeholder fairness in recommender systems and the S'mores framework—a simulation allowing users to choose between mainstream and niche algorithms. His research shows specialized recommenders improve utility for niche users while raising questions abo ...  Show more

はじめまして！podcastはじめました！今日はこのpodcastと自分の紹介です。 today’s topic is an introduction of me and this podcast!応援してくれると嬉しいです！ https://ko-fi.com/tomo_ltj 

In this podcast, I deliberately use examples to review many of the HY cognitive errors that are often tested on the USMLEs. I introduce these errors with an example, discuss the error, and then mention specific hotspots that the USMLEs use to test that particular error type. At t ...  Show more

Mit uns kannst Du nebenbei Deutsch lernen. Wir sind, Virpi und Sandra, deine zertifizierten Dozentinnen für die Hosentasche.

Fehler passieren jedem, Fehler sind nicht zu vermeiden und durch Fehler lernen wir. Wie man richtig mit Fehlern umgehen kann besprechen Virpi und Sandra ...

We're back! This week we are talking about brand and influencer events, what makes and good or bad one and if really we are just too lazy for them! Learn more about your ad choices. Visit megaphone.fm/adchoices