Cuttlefish Model Tuning
Data Skeptic21 Aug 2023

Cuttlefish Model Tuning

Hongyi Wang, a Senior Researcher at the Machine Learning Department at Carnegie Mellon University, joins us. His research is in the intersection of systems and machine learning. He discussed his research paper, Cuttlefish: Low-Rank Model Training without All the Tuning, on today's show.

Hogyi started by sharing his thoughts on whether developers need to learn how to fine-tune models. He then spoke about the need to optimize the training of ML models, especially as these models grow bigger. He discussed how data centers have the hardware to train these large models but not the community. He then spoke about the Low-Rank Adaptation (LoRa) technique and where it is used.

Hongyi discussed the Cuttlefish model and how it edges LoRa. He shared the use cases of Cattlefish and who should use it. Rounding up, he gave his advice on how people can get into the machine learning field. He also shared his future research ideas.

Det här avsnittet är hämtat från ett öppet RSS-flöde och publiceras inte av Podme. Det kan innehålla reklam.

Avsnitt(601)

Video Recommendations in Industry

Video Recommendations in Industry

In this episode, Kyle Polich sits down with Cory Zechmann, a content curator working in streaming television with 16 years of experience running the music blog "Silence Nogood." They explore the inter...

26 Dec 202538min

Eye Tracking in Recommender Systems

Eye Tracking in Recommender Systems

In this episode, Santiago de Leon takes us deep into the world of eye tracking and its revolutionary applications in recommender systems. As a researcher at the Kempelin Institute and Brno University,...

18 Dec 202552min

Cracking the Cold Start Problem

Cracking the Cold Start Problem

In this episode of Data Skeptic, we dive deep into the technical foundations of building modern recommender systems. Unlike traditional machine learning classification problems where you can simply ap...

8 Dec 202539min

Designing Recommender Systems for Digital Humanities

Designing Recommender Systems for Digital Humanities

In this episode of Data Skeptic, we explore the fascinating intersection of recommender systems and digital humanities with guest Florian Atzenhofer-Baumgartner, a PhD student at Graz University of Te...

23 Nov 202536min

DataRec Library for Reproducible in Recommend Systems

DataRec Library for Reproducible in Recommend Systems

In this episode of Data Skeptic's Recommender Systems series, host Kyle Polich explores DataRec, a new Python library designed to bring reproducibility and standardization to recommender systems resea...

13 Nov 202532min

Shilling Attacks on Recommender Systems

Shilling Attacks on Recommender Systems

In this episode of Data Skeptic's Recommender Systems series, Kyle sits down with Aditya Chichani, a senior machine learning engineer at Walmart, to explore the darker side of recommendation algorithm...

5 Nov 202534min

Music Playlist Recommendations

Music Playlist Recommendations

In this episode, Rebecca Salganik, a PhD student at the University of Rochester with a background in vocal performance and composition, discusses her research on fairness in music recommendation syste...

29 Okt 202552min

Bypassing the Popularity Bias

Bypassing the Popularity Bias

15 Okt 202534min

Populärt inom Vetenskap

p3-dystopia
dumma-manniskor
allt-du-velat-veta
kapitalet-en-podd-om-ekonomi
sexet
rss-ufobortom-rimligt-tvivel
rss-vetenskapsradion
svd-nyhetsartiklar
medicinvetarna
rss-vetenskapsradion-2
det-morka-psyket
ufo-sverige
rss-spraket
hacka-livet
paranormalt-med-caroline-giertz
halsorevolutionen
barnpsykologerna
ideer-som-forandrar-varlden
rss-klotet
pojkmottagningen