Training on the Edge: The why and the how. - Navjot Kukreja; Alena Shilova; Olivier Beaumont; Jan Hückelheim; Nicola J. Ferrier; Paul D. Hovland; Gerard Gorman (IPDPS Workshops, 2019)

Optimal checkpointing for heterogeneous chains: how to train deep neural networks with limited memory. - Olivier Beaumont; Lionel Eyraud-Dubois; Julien Herrmann; Alexis Joly; Alena Shilova (CoRR, 2019)

Optimal GPU-CPU Offloading Strategies for Deep Neural Network Training. - Olivier Beaumont; Lionel Eyraud-Dubois; Alena Shilova (Euro-Par, 2020)

A Makespan Lower Bound for the Tiled Cholesky Factorization Based on ALAP Schedule. - Olivier Beaumont; Julien Langou; Willy Quach; Alena Shilova (Euro-Par, 2020)

Pipelined Model Parallelism: Complexity Results and Memory Considerations. - Olivier Beaumont; Lionel Eyraud-Dubois; Alena Shilova (Euro-Par, 2021)

Memory Efficient Deep Neural Network Training. - Alena Shilova (Euro-Par Workshops, 2021)

Efficient Combination of Rematerialization and Offloading for Training DNNs. - Olivier Beaumont; Lionel Eyraud-Dubois; Alena Shilova (NeurIPS, 2021)

Memory Saving Strategies for Deep Neural Network Training. (Stratégies pour économiser la mémoire lors de l'apprentissage dans les réseaux neuronaux profonds). - Alena Shilova (2021)

Survey on Efficient Training of Large Neural Networks. - Julia Gusak; Daria Cherniuk; Alena Shilova; Alexandr Katrutsa; Daniel Bershatsky; Xunyi Zhao; Lionel Eyraud-Dubois; Oleh Shliazhko; Denis Dimitrov; Ivan V. Oseledets; Olivier Beaumont (IJCAI, 2022)

MadPipe: Memory Aware Dynamic Programming Algorithm for Pipelined Model Parallelism. - Olivier Beaumont; Lionel Eyraud-Dubois; Alena Shilova (IPDPS Workshops, 2022)

Survey on Large Scale Neural Network Training. - Julia Gusak; Daria Cherniuk; Alena Shilova; Alexandr Katrutsa; Daniel Bershatsky; Xunyi Zhao; Lionel Eyraud-Dubois; Oleg Shlyazhko; Denis Dimitrov; Ivan V. Oseledets; Olivier Beaumont (CoRR, 2022)

Entropy Regularized Reinforcement Learning with Cascading Networks. - Riccardo Della Vecchia; Alena Shilova; Philippe Preux; Riad Akrour (CoRR, 2022)

AdaStop: sequential testing for efficient and reliable comparisons of Deep RL Agents. - Timothée Mathieu; Riccardo Della Vecchia; Alena Shilova; Matheus Centa de Medeiros; Hector Kohler; Odalric-Ambrym Maillard; Philippe Preux (CoRR, 2023)

AdaStop: adaptive statistical testing for sound comparisons of Deep RL agents. - Timothée Mathieu; Matheus Centa; Riccardo Della Vecchia; Hector Kohler; Alena Shilova; Odalric-Ambrym Maillard; Philippe Preux (Trans. Mach. Learn. Res., 2024)

Optimal Re-Materialization Strategies for Heterogeneous Chains: How to Train Deep Neural Networks with Limited Memory. - Olivier Beaumont; Lionel Eyraud-Dubois; Julien Herrmann; Alexis Joly; Alena Shilova (ACM Trans. Math. Softw., 2024)

StaQ it! Growing neural networks for Policy Mirror Descent. - Alena Shilova; Alex Davey; Brahim Driss; Riad Akrour (CoRR, 2025)