1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
Intractability of Learning the Discrete Logarithm with Gradient-Based Methods
Rustem Takhanov, Maxat Tezekbayev, Artur Pak +3
The discrete logarithm problem is a fundamental challenge in number theory with significant implications for cryptographic protocols. In this paper, we investigate the limitations…
cs.LG2023★ 1 cited
Long-Tail Theory under Gaussian Mixtures
Arman Bolatov, Maxat Tezekbayev, Igor Melnykov +3
We suggest a simple Gaussian mixture model for data generation that complies with Feldman's long tail theory (2020). We demonstrate that a linear classifier cannot decrease the gen…