1 citations · 3 across the 8 of their papers we have counts for
8 papers
Byzantine-Robust Optimization under -Smoothness
Arman Bolatov, Samuel Horváth, Martin Takáč +1
We consider distributed optimization under Byzantine attacks in the presence of -smoothness, a generalization of standard -smoothness that captures functions with sta…
Simplex Deep Linear Discriminant Analysis
Maxat Tezekbayev, Arman Bolatov, Zhenisbek Assylbekov
We revisit Deep Linear Discriminant Analysis (Deep LDA) from a likelihood-based perspective. While classical LDA is a simple Gaussian model with linear decision boundaries, attachi…
Deep Linear Discriminant Analysis Revisited
Maxat Tezekbayev, Rustem Takhanov, Arman Bolatov +1
We show that for unconstrained Deep Linear Discriminant Analysis (LDA) classifiers, maximum-likelihood training admits pathological solutions in which class means drift together, c…
Overspecified Mixture Discriminant Analysis: Exponential Convergence, Statistical Guarantees, and Remote Sensing Applications
Arman Bolatov, Alan Legg, Igor Melnykov +3
This study explores the classification error of Mixture Discriminant Analysis (MDA) in scenarios where the number of mixture components exceeds those present in the actual data dis…
Who to Trust? Aggregating Client Predictions in Federated Distillation
Viktor Kovalchuk, Denis Son, Arman Bolatov +6
Under data heterogeneity (e.g., ), clients may produce unreliable predictions for instances belonging to unfamiliar classes. An equally weighted combinatio…
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…
Gradient Descent Fails to Learn High-frequency Functions and Modular Arithmetic
Rustem Takhanov, Maxat Tezekbayev, Artur Pak +2
Classes of target functions containing a large number of approximately orthogonal elements are known to be hard to learn by the Statistical Query algorithms. Recently this classica…
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…