activity
20172026
most citedA Critique of the Smooth Inverse Frequency Sentence Embeddings

3 citations · 6 across the 12 of their papers we have counts for

collaborators

18 papers

cs.IT2026

Structure of kissing arrangements in and a place for the st sphere

Rustem Takhanov, Zhenisbek Assylbekov, Stanislav Yun

Most currently known kissing arrangements of size in share a common structure. They consist of vectors supported on , an…

cs.LG2026

Conditional KRR: Injecting Unpenalized Features into Kernel Methods with Applications to Kernel Thresholding

Rustem Takhanov, Zhenisbek Assylbekov

Conditionally positive definite (CPD) kernels are defined with respect to a function class . It is well known that such a kernel is associated with its native spac…

stat.ML2026

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…

stat.ML2026

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…

stat.ML2025

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…

stat.ML2025

Learning Overspecified Gaussian Mixtures Exponentially Fast with the EM Algorithm

Zhenisbek Assylbekov, Alan Legg, Artur Pak

We investigate the convergence properties of the EM algorithm when applied to overspecified Gaussian mixture models -- that is, when the number of components in the fitted model ex…