20 citations · 31 across the 18 of their papers we have counts for
6 papers · 1 filter
Posterior Frequencies and the Cost of Not Fitting: A Correction to a Memorization Lower Bound
Zhenisbek Assylbekov, Rustem Takhanov
Feldman's memorization lower bound assigns a frequency coefficient based on how often a point appears in the training sample. We give an exact three-point counterexample to its con…
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…
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…
Context Vectors are Reflections of Word Vectors in Half the Dimensions
Zhenisbek Assylbekov, Rustem Takhanov
This paper takes a step towards theoretical analysis of the relationship between word embeddings and context embeddings in models such as word2vec. We start from basic probabilisti…