FRUGAL: Memory-Efficient Optimization by Reducing State Overhead for Scalable Training. - Philip Zmushko; Aleksandr Beznosikov; Martin Takác 001; Samuel Horváth (CoRR, 2024)

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning. - Andrei Semenov; Philip Zmushko; Alexander Pichugin; Aleksandr Beznosikov (CoRR, 2024)

Label Privacy in Split Learning for Large Models with Parameter-Efficient Training. - Philip Zmushko; Marat Mansurov; Ruslan Svirschevski; Denis Kuznedelev; Max Ryabinin; Aleksandr Beznosikov (CoRR, 2024)

Sign Operator for Coping with Heavy-Tailed Noise: High Probability Convergence Bounds with Extensions to Distributed Optimization and Comparison Oracle. - Nikita Kornilov; Philip Zmushko; Andrei Semenov; Alexander V. Gasnikov; Aleksandr Beznosikov (CoRR, 2025)

Sign-SGD is the Golden Gate between Multi-Node to Single-Node Learning: Significant Boost via Parameter-Free Optimization. - Daniil Medyakov; Sergey Stanko; Gleb Molodtsov; Philip Zmushko; Grigoriy Evseev; Egor Petrov; Aleksandr Beznosikov (CoRR, 2025)