Daniil Dmitriev

According to our database, Daniil Dmitriev authored at least 9 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Randomstrasse101: Open Problems of 2025.

Afonso S. Bandeira, Daniil Dmitriev, Kevin Lucca, Petar Nizic-Nikolac, Almut Rödder

CoRR, March, 2026

Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees.

Daniil Dmitriev, Zhihan Huang, Yuting Wei

CoRR, February, 2026

Learning in an Echo Chamber: Online Learning with Replay Adversary.

Daniil Dmitriev, Harald Eskelund Franck, Carolin Heinzler, Amartya Sanyal

Proceedings of the 2026 Annual ACM-SIAM Symposium on Discrete Algorithms, 2026

2024

Robust Mixture Learning when Outliers Overwhelm Small Groups.

Daniil Dmitriev, Rares-Darius Buhai, Stefan Tiegel, Alexander Wolters, Gleb Novikov, Amartya Sanyal, David Steurer, Fanny Yang

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Asymptotics of Learning with Deep Structured (Random) Features.

Dominik Schröder, Daniil Dmitriev, Hugo Cui, Bruno Loureiro

Proceedings of the Forty-first International Conference on Machine Learning, 2024

On the Growth of Mistakes in Differentially Private Online Learning: A Lower Bound Perspective.

Daniil Dmitriev, Kristóf Szabó, Amartya Sanyal

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Greedy Heuristics and Linear Relaxations for the Random Hitting Set Problem.

Gabriel Arpino, Daniil Dmitriev, Nicolò Grometto

Proceedings of the Approximation, 2024

2023

Deterministic equivalent and error universality of deep random features learning.

Dominik Schröder, Hugo Cui, Daniil Dmitriev, Bruno Loureiro

Proceedings of the International Conference on Machine Learning, 2023

2020

Dynamic Model Pruning with Feedback.

Tao Lin, Sebastian U. Stich, Luis Barba, Daniil Dmitriev, Martin Jaggi

Proceedings of the 8th International Conference on Learning Representations, 2020