Maksim Velikanov

According to our database, Maksim Velikanov authored at least 13 papers between 2021 and 2026.

Collaborative distances:

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

2026

Learnable Multipliers: Freeing the Scale of Language Model Matrix Layers.

Maksim Velikanov, Ilyas Chahed, Jingwei Zuo, Dhia Eddine Rhaiem, Younes Belkada, Hakim Hacid

CoRR, January, 2026

2025

Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance.

Jingwei Zuo, Maksim Velikanov, Ilyas Chahed, Younes Belkada, Dhia Eddine Rhayem, Guillaume Kunsch, Hakim Hacid, Hamza Yous, Brahim Farhat, Ibrahim Khadraoui, Mugariya Farooq, Giulia Campesan, Ruxandra Cojocaru, Yasser Dahou, Shi Hu, Iheb Chaabane, Puneesh Khanna, Mohamed El Amine Seddik, Ngoc Dung Huynh, Phuc H. Le-Khac, Leen Al Qadi, Billel Mokeddem, Mohamed Chami, Abdalgader Abubaker, Mikhail Lubinets, Kacper Piskorski, Slim Frikha

CoRR, July, 2025

SGD with memory: fundamental properties and stochastic acceleration.

Dmitry Yarotsky, Maksim Velikanov

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions.

Maksim Velikanov, Dmitry Yarotsky

J. Mach. Learn. Res., 2024

Falcon Mamba: The First Competitive Attention-free 7B Language Model.

Jingwei Zuo, Maksim Velikanov, Dhia Eddine Rhaiem, Ilyas Chahed, Younes Belkada, Guillaume Kunsch, Hakim Hacid

CoRR, 2024

Falcon2-11B Technical Report.

Quentin Malartic, Nilabhra Roy Chowdhury, Ruxandra Cojocaru, Mugariya Farooq, Giulia Campesan, Yasser Abdelaziz Dahou Djilali, Sanath Narayan, Ankit Singh, Maksim Velikanov, Basma El Amel Boussaha, Mohammed Al-Yafeai, Hamza Alobeidli, Leen Al Qadi, Mohamed El Amine Seddik, Kirill Fedyanin, Réda Alami, Hakim Hacid

CoRR, 2024

Generalization error of spectral algorithms.

Maksim Velikanov, Maxim Panov, Dmitry Yarotsky

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Efficient Conformal Prediction under Data Heterogeneity.

Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác, Eric Moulines, Maxim Panov

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Comparing the robustness of modern no-reference image- and video-quality metrics to adversarial attacks.

Anastasia Antsiferova, Khaled Abud, Aleksandr Gushchin, Sergey Lavrushkin, Ekaterina Shumitskaya, Maksim Velikanov, Dmitriy S. Vatolin

CoRR, 2023

A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta.

Maksim Velikanov, Denis Kuznedelev, Dmitry Yarotsky

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Embedded Ensembles: infinite width limit and operating regimes.

Maksim Velikanov, Roman V. Kail, Ivan Anokhin, Roman Vashurin, Maxim Panov, Alexey Zaytsev, Dmitry Yarotsky

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Universal scaling laws in the gradient descent training of neural networks.

Maksim Velikanov, Dmitry Yarotsky

CoRR, 2021

Explicit loss asymptotics in the gradient descent training of neural networks.

Maksim Velikanov, Dmitry Yarotsky

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021