Sasha Abramowitz

According to our database, Sasha Abramowitz authored at least 8 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Multi-Agent Reinforcement Learning with Selective State-Space Models.

Jemma Daniel, Ruan de Kock, Louay Ben Nessir, Sasha Abramowitz, Omayma Mahjoub, Wiem Khlifi, Claude Formanek, Arnu Pretorius

CoRR, 2024

Performant, Memory Efficient and Scalable Multi-Agent Reinforcement Learning.

Omayma Mahjoub, Sasha Abramowitz, Ruan de Kock, Wiem Khlifi, Simon du Toit, Jemma Daniel, Louay Ben Nessir, Louise Beyers, Claude Formanek, Liam Clark, Arnu Pretorius

CoRR, 2024

Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX.

Clément Bonnet, Daniel Luo, Donal Byrne, Shikha Surana, Sasha Abramowitz, Paul Duckworth, Vincent Coyette, Laurence Illing Midgley, Elshadai Tegegn, Tristan Kalloniatis, Omayma Mahjoub, Matthew Macfarlane, Andries P. Smit, Nathan Grinsztajn, Raphaël Boige, Cemlyn N. Waters, Mohamed A. Mimouni, Ulrich A. Mbou Sob, Ruan de Kock, Siddarth Singh, Daniel Furelos-Blanco, Victor Le, Arnu Pretorius, Alexandre Laterre

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Generalisable Agents for Neural Network Optimisation.

Kale-ab Tessera, Callum Rhys Tilbury, Sasha Abramowitz, Ruan de Kock, Omayma Mahjoub, Benjamin Rosman, Sara Hooker, Arnu Pretorius

CoRR, 2023

Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX.

Clément Bonnet, Daniel Luo, Donal Byrne, Shikha Surana, Vincent Coyette, Paul Duckworth, Laurence I. Midgley, Tristan Kalloniatis, Sasha Abramowitz, Cemlyn N. Waters, Andries P. Smit, Nathan Grinsztajn, Ulrich A. Mbou Sob, Omayma Mahjoub, Elshadai Tegegn, Mohamed A. Mimouni, Raphaël Boige, Ruan de Kock, Daniel Furelos-Blanco, Victor Le, Arnu Pretorius, Alexandre Laterre

CoRR, 2023

2022

Scalable evolutionary hierarchical reinforcement learning.

Sasha Abramowitz, Geoff Nitschke

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Towards Run-time Efficient Hierarchical Reinforcement Learning.

Sasha Abramowitz, Geoff Nitschke

Proceedings of the IEEE Congress on Evolutionary Computation, 2022

2020

Efficiently Coevolving Deep Neural Networks and Data Augmentations.

Shane Acton, Sasha Abramowitz, Liron Toledo, Geoff Nitschke

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020