Tile Low Rank Cholesky Factorization for Climate/Weather Modeling Applications on Manycore Architectures. - Kadir Akbudak; Hatem Ltaief; Aleksandr Mikhalev; David E. Keyes (ISC, 2017)

Exploiting Data Sparsity for Large-Scale Matrix Computations. - Kadir Akbudak; Hatem Ltaief; Aleksandr Mikhalev; Ali Charara 001; Aniello Esposito; David E. Keyes (Euro-Par, 2018)

Comparative Studies Between Hydrothermal Carbonation and Torrefaction for Biofuel Production from Poultry Litter. - Rafail Isemin; Aleksandr Mikhalev; Oleg Milovanov; Dmitry Klimov; Natalia Muratova; Kristina Krysanova; Yuri Teplitskii; Anatolii Greben'kov; Vadim Kogh-Tatarenko (ICBBB, 2019)

Performance Analysis of Tile Low-Rank Cholesky Factorization Using PaRSEC Instrumentation Tools. - Qinglei Cao; Yu Pei; Thomas Hérault; Kadir Akbudak; Aleksandr Mikhalev; George Bosilca; Hatem Ltaief; David E. Keyes; Jack J. Dongarra (ProTools@SC, 2019)

Extreme-Scale Task-Based Cholesky Factorization Toward Climate and Weather Prediction Applications. - Qinglei Cao; Yu Pei; Kadir Akbudak; Aleksandr Mikhalev; George Bosilca; Hatem Ltaief; David E. Keyes; Jack J. Dongarra (PASC, 2020)

Memory-Efficient Backpropagation through Large Linear Layers. - Daniel Bershatsky; Aleksandr Mikhalev; Alexandr Katrutsa; Julia Gusak; Daniil Merkulov; Ivan V. Oseledets (CoRR, 2022)

Run LoRA Run: Faster and Lighter LoRA Implementations. - Daria Cherniuk; Aleksandr Mikhalev; Ivan V. Oseledets (CoRR, 2023)

SparseGrad: A Selective Method for Efficient Fine-tuning of MLP Layers. - Viktoria Chekalina; Anna Rudenko; Gleb Mezentsev; Aleksandr Mikhalev; Alexander Panchenko; Ivan V. Oseledets (EMNLP, 2024)

Quantization of Large Language Models with an Overdetermined Basis. - Daniil Merkulov; Daria Cherniuk; Alexander Rudikov; Ivan V. Oseledets; Ekaterina A. Muravleva; Aleksandr Mikhalev; Boris Kashin (UAI, 2024)

LoTR: Low Tensor Rank Weight Adaptation. - Daniel Bershatsky; Daria Cherniuk; Talgat Daulbaev; Aleksandr Mikhalev; Ivan V. Oseledets (CoRR, 2024)

NNTile: a machine learning framework capable of training extremely large GPT language models on a single node. - Aleksandr Mikhalev; Aleksandr Katrutsa; Konstantin Sozykin; Ivan V. Oseledets (CoRR, 2025)