Sotabase

Career

· HFC Gen AI Program, Scale AI2025–2025
· Machine Learning Intern, Stealth AI Startup2025–2025
· Doctor of Philosophy - PhD, Computer Science, Caltech2021–2026
· PhD Candidate In CS, Caltech (Current)2021–
· PHD Student, Caltech (Current)2021–

Publications (16)

Regularized Linear Regression for Binary Classification
2023
9
cited
On uniform Hilbert Schmidt stability of groups
2020
8
cited
Right exact localizations of groups
2019
7
cited
Maximums of the Additive Differential Probability of Exclusive-Or
2021
6
cited
A Novel Gaussian Min–Max Theorem and Its Applications
2024
4
cited
One-Bit Quantization and Sparsification for Multiclass Linear Classification via Regularized Regression
2024
2
cited
Connectedness of loss landscapes via the lens of Morse theory
2022
1
cited
Homologies of inverse limits of groups
2018
1
cited
One-Bit Quantization and Sparsification for Multiclass Linear Classification With Strong Regularization
2025
1
cited
Self-derived localizations of groups
2019
1
cited
A Precise Performance Analysis of the Randomized Singular Value Decomposition
2025
Gaussian Universality for Diffusion Models
2025
One-Bit Quantization for Random Features Models
2025
Robust Mean Estimation With Auxiliary Samples
2025
The Generalization Error of Stochastic Mirror Descent on Over-Parametrized Linear Models
arXiv.org · 2023
Universality in Transfer Learning for Linear Models
2024
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Danil Akhtiamov | Researcher Profile | Sotabase | Sotabase