Front

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 interest is multitask learning and multi-objective optimization.

News

• Two papers accepted at ICML 2023:
  • Equivariant Architectures for Learning in Deep Weight Spaces (Oral).
  • Auxiliary Learning as an Asymmetric Bargaining Game.
• Multi-Task Learning as a Bargaining Game has been accepted at ICML 2022.
• Personalized Federated Learning with Gaussian Processes accepted to NeurIPS 2021.
• Two papers to be presented at ICML 2021:
  • Personalized Federated Learning using Hypernetworks.
  • GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning.
• Two papers to be presented at ICLR 2021:
  • Learning the Pareto Front with Hypernetworks.
  • Auxiliary Learning by Implicit Differentiation.

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.