Researcher

Zhenisbek Assylbekov

Educator and Researcher in ML/Stats

Fort Wayne, Kazakhstan

Research focus

Purdue University Fort WayneFort Wayne, Kazakhstan

My current research focuses on the fundamental aspects of learning, specifically exploring benign overfitting, long-tailed distributions, and the hardness of learning.

Statistics

NLP

Publications

Approved public publications linked to this researcher profile.

14 publications

Latest Citations

Learning Overspecified Gaussian Mixtures Exponentially Fast with the EM Algorithm
Lecture Notes in Computer Science - 2025 - OpenAlex00 citations
Open
Convergence of the EM algorithm in KL distance for overspecified Gaussian mixtures
Statistical Papers - 2025 - OpenAlex01 citation
Open
Classifier Performance on Long‐Tail Distributions
Statistical Analysis and Data Mining The ASA Data Science Journal - 2025 - OpenAlex00 citations
Open
Gradient descent fails to learn high-frequency functions and modular arithmetic
Machine Learning - 2025 - OpenAlex01 citation
Open
Long-Tail Theory Under Gaussian Mixtures
Frontiers in artificial intelligence and applications - 2023 - OpenAlex01 citation
Open
Hardness of Learning AES with Gradient-Based Methods
Lecture Notes in Computer Science - 2023 - OpenAlex00 citations
Open
CONVERGENCE OF THE PARTITION FUNCTION IN THE STATIC WORD EMBEDDING MODEL
EURASIAN MATHEMATICAL JOURNAL - 2022 - OpenAlex00 citations
Open
From Hyperbolic Geometry Back to Word Embeddings
arXiv (Cornell University) - 2022 - OpenAlex01 citation
Open
Approximation error of<scp>Fourier</scp>neural networks
Statistical Analysis and Data Mining: The ASA Data Science Journal - 2021 - OpenAlex01 citation
Open
Intractability of Learning the Discrete Logarithm with Gradient-Based Methods - ASIAN CONFERENCE ON MACHINE LEARNING, VOL 222, 2023
2023 - OpenAlex01 citation
Open
The Rediscovery Hypothesis: Language Models Need to Meet Linguistics - JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 2021
2021 - OpenAlex04 citations
Open
Context Vectors Are Reflections of Word Vectors in Half the Dimensions - PROCEEDINGS OF THE TWENTY-NINTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INT, 2020
2020 - OpenAlex00 citations
Open
A Critique of the Smooth Inverse Frequency Sentence Embeddings (Student Abstract) - THIRTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THE THIRTY-SECOND INNO, 2020
2020 - OpenAlex00 citations
Open
Fourier neural networks: A comparative study - INTELLIGENT DATA ANALYSIS, 2020
2020 - OpenAlex020 citations
Open

Regional connection

DSML member