[ContinualAI Reading group]: "Class-Incremental Learning with Generative Classifiers"

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Keiland Cooper

May 17, 2021, 8:21:03 AM5/17/21
to Continual Learning & AI News
Hi All,

This Friday 21-05-2021, 5.30pm CEST, for the ContinualAI Reading Group, Gido M. van de Ven  will present the paper:

Abstract: Incrementally training deep neural networks to recognize new classes is a challenging problem. Most existing class-incremental learning methods store data or use generative replay, both of which have drawbacks, while 'rehearsal-free' alternatives such as parameter regularization or bias-correction methods do not consistently achieve high performance. Here, we put forward a new strategy for class-incremental learning: generative classification. Rather than directly learning the conditional distribution p(y|x), our proposal is to learn the joint distribution p(x,y), factorized as p(x|y)p(y), and to perform classification using Bayes' rule. As a proof-of-principle, here we implement this strategy by training a variational autoencoder for each class to be learned and by using importance sampling to estimate the likelihoods p(x|y). This simple approach performs very well on a diverse set of continual learning benchmarks, outperforming generative replay and other existing baselines that do not store data.

The event will be moderated by: Vincenzo Lomonaco

- Eventbrite event (to save it in you calendar and get reminders): Click Here 
- Microsoft Teams: click here to join 
- YouTube recordings of the previous sessions: https://www.youtube.com/c/ContinualAI

Feel free to share this email to anyone interested and invite them to subscribe this mailing-list here: https://groups.google.com/g/continualai 

Please also contact me if you want to speak at one of the next sessions!

Looking forward to seeing you all there!

All the best,
Keiland Cooper

University of California
ContinualAI Co-founding Board Member

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