About me

I am a PhD student at Bar Ilan University, working under the joint supervision of Prof. Gal Chechik, head of the Computational Neurobiology Lab at the Gonda Multidisciplinary Brain Research Center, and Prof. Ethan Fetaya from the Faculty of Engineering. My main research interests are multitask learning and multi-objective optimization.

News

Publications

Multi-Task Learning as a Bargaining Game
A. Navon, A. Shamsian, I. Achituve, H. Maron, K. Kawaguchi, G. Chechik, E. Fetaya
International Conference on Machine Learning, ICML, 2022.

Personalized Federated Learning using Hypernetworks
A. Shamsian, A. Navon, G. Chechik, E. Fetaya
International Conference on Machine Learning, ICML, 2021.

Personalized Federated Learning with Gaussian Processes
I. Achituve, A. Shamsian, A. Navon, G. Chechik, E. Fetaya
Neural Information Processing Systems, NeurIPS 2021.

GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning
I. Achituve, A. Navon, Y. Yemini, G. Chechik, E. Fetaya
International Conference on Machine Learning, ICML 2021.

Learning the Pareto Front with Hypernetworks
A. Navon, A. Shamsian, G. Chechik, E. Fetaya
International Conference on Learning Representations, ICLR 2021.

Auxiliary Learning by Implicit Differentiation
A. Navon, I. Achituve, H. Maron, G. Chechik, E. Fetaya
International Conference on Learning Representations, ICLR 2021.

Capturing Between-Tasks Covariance and Similarities Using Multivariate Linear Mixed Models
A. Navon, S. Rosset
Electronic Journal of Statistics, EJS 2020.

Preprints

Equivariant Architectures for Learning in Deep Weight Spaces
A. Navon, A. Shamsian, I. Achituve, E. Fetaya, G. Chechik, H. Maron
Preprint, 2023.

Auxiliary Learning as an Asymmetric Bargaining Game
A. Shamsian, A. Navon, N. Glazer, K. Kawaguchi, G. Chechik, E. Fetaya
Preprint, 2023.

A Study on the Evaluation of Generative Models
E. Betzalel, C. Penso, A. Navon, E. Fetaya
Preprint, 2022.