University of Cambridge > Talks.cam > Computational Neuroscience > Frugal computation

  Browse A-Z

Log in

Googledetails Microsoftdetails

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹ️ Information

Frugal computation

Download to your calendar using vCal

If you have a question about this talk, please contact Daniel Kornai .

The brain implements algorithms that choose smart actions to achieve its goals, using a tiny fraction of the power used by today’s computers on comparable tasks. Modeling these algorithms requires us to account not only for the task demands, but also for the costs of thinking. We call this problem setting “frugal computation”. I will describe two studies that incorporate computational costs into control problems. Specifically, we generalize past work on efficient coding and predictive coding, by accounting for either the representational costs of integrating information or the computational costs of performing that integration. We find that the predictability of the system determines phase transitions between strategies, showing when it is worth spending computational resources to achieve better performance.

This talk is part of the Computational Neuroscience series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

Georaphy Department Seminar Room Online via zoom & Kings Hedges Room International Cafe Scientifique

Other talks

Morning Tea and Coffee Title and abstract tba TBC Discussion I Cooperation in Nature Clonal haematopoiesis, early detection and pre-leukemia to leukemia development
 

© 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity