A Statistical Model for Measuring Structural Similarity between Webpages. - Zhenisbek Assylbekov; Assulan Nurkas; Inês Russinho Mouga (RANLP, 2015)

Detecting Value-Added Tax Evasion by Business Entities of Kazakhstan. - Zhenisbek Assylbekov; Igor Melnykov; Rustam Bekishev; Assel Baltabayeva; Dariya Bissengaliyeva; Eldar Mamlin (KES-IDT (1), 2016)

Simple and Accurate Method for Parallel Web Pages Detection. - Alibi Jangeldin; Zhenisbek Assylbekov (ACIIDS (1), 2017)

Syllable-aware Neural Language Models: A Failure to Beat Character-aware Ones. - Zhenisbek Assylbekov; Rustem Takhanov; Bagdat Myrzakhmetov; Jonathan North Washington (EMNLP, 2017)

Patterns Versus Characters in Subword-Aware Neural Language Modeling. - Rustem Takhanov; Zhenisbek Assylbekov (ICONIP (2), 2017)

Reproducing and Regularizing the SCRN Model. - Olzhas Kabdolov; Zhenisbek Assylbekov; Rustem Takhanov (COLING, 2018)

Manual vs Automatic Bitext Extraction. - Aibek Makazhanov; Bagdat Myrzakhmetov; Zhenisbek Assylbekov (LREC, 2018)

Reusing Weights in Subword-Aware Neural Language Models. - Zhenisbek Assylbekov; Rustem Takhanov (NAACL-HLT, 2018)

Initial Explorations on Chaotic Behaviors of Recurrent Neural Networks. - Bagdat Myrzakhmetov; Rustem Takhanov; Zhenisbek Assylbekov (CICLing (1), 2019)

Low-Rank Approximation of Matrices for PMI-Based Word Embeddings. - Alena Sorokina; Aidana Karipbayeva; Zhenisbek Assylbekov (CICLing (1), 2019)

A Critique of the Smooth Inverse Frequency Sentence Embeddings. - Aidana Karipbayeva; Alena Sorokina; Zhenisbek Assylbekov (CoRR, 2019)

Semantics- and Syntax-related Subvectors in the Skip-gram Embeddings. - Maxat Tezekbayev; Zhenisbek Assylbekov; Rustem Takhanov (CoRR, 2019)

Context Vectors are Reflections of Word Vectors in Half the Dimensions. - Zhenisbek Assylbekov; Rustem Takhanov (J. Artif. Intell. Res., 2019)

A Critique of the Smooth Inverse Frequency Sentence Embeddings (Student Abstract). - Aidana Karipbayeva; Alena Sorokina; Zhenisbek Assylbekov (AAAI, 2020)

Semantics- and Syntax-Related Subvectors in the Skip-Gram Embeddings (Student Abstract). - Maxat Tezekbayev; Zhenisbek Assylbekov; Rustem Takhanov (AAAI, 2020)

Squashed Shifted PMI Matrix: Bridging Word Embeddings and Hyperbolic Spaces. - Zhenisbek Assylbekov; Alibi Jangeldin (Australasian Conference on Artificial Intelligence, 2020)

Context Vectors Are Reflections of Word Vectors in Half the Dimensions (Extended Abstract). - Zhenisbek Assylbekov; Rustem Takhanov (IJCAI, 2020)

Binarized PMI Matrix: Bridging Word Embeddings and Hyperbolic Spaces. - Zhenisbek Assylbekov; Alibi Jangeldin (CoRR, 2020)

Fourier neural networks: A comparative study. - Malika Uteuliyeva; Abylay Zhumekenov; Rustem Takhanov; Zhenisbek Assylbekov; Alejandro J. Castro; Olzhas Kabdolov (Intell. Data Anal., 2020)

Hyperbolic Embedding for Finding Syntax in BERT. - Temirlan Auyespek; Thomas Mach; Zhenisbek Assylbekov (DP@AI*IA, 2021)

Geometric Probing of Word Vectors. - Madina Babazhanova; Maxat Tezekbayev; Zhenisbek Assylbekov (ESANN, 2021)

The Rediscovery Hypothesis: Language Models Need to Meet Linguistics. - Vassilina Nikoulina; Maxat Tezekbayev; Nuradil Kozhakhmet; Madina Babazhanova; Matthias Gallé; Zhenisbek Assylbekov (J. Artif. Intell. Res., 2021)

Approximation error of Fourier neural networks. - Abylay Zhumekenov; Rustem Takhanov; Alejandro J. Castro; Zhenisbek Assylbekov (Stat. Anal. Data Min., 2021)

Hardness of Learning AES Key (Short Paper). - Sultan Nurmukhamedov; Artur Pak; Rustem Takhanov; Zhenisbek Assylbekov (DP@AI*IA, 2022)

Speeding Up Entmax. - Maxat Tezekbayev; Vassilina Nikoulina; Matthias Gallé; Zhenisbek Assylbekov (NAACL-HLT (Findings), 2022)

From Hyperbolic Geometry Back to Word Embeddings. - Zhenisbek Assylbekov; Sultan Nurmukhamedov; Arsen Sheverdin; Thomas Mach (RepL4NLP@ACL, 2022)

Hardness of Learning AES Key (Student Abstract). - Artur Pak; Sultan Nurmukhamedov; Rustem Takhanov; Zhenisbek Assylbekov (AAAI, 2023)

Intractability of Learning the Discrete Logarithm with Gradient-Based Methods. - Rustem Takhanov; Maxat Tezekbayev; Artur Pak; Arman Bolatov; Zhibek Kadyrsizova; Zhenisbek Assylbekov (ACML, 2023)

Hardness of Learning AES with Gradient-Based Methods. - Kanat Alimanov; Zhenisbek Assylbekov (CANS, 2023)

Long-Tail Theory Under Gaussian Mixtures. - Arman Bolatov; Maxat Tezekbayev; Igor Melnykov; Artur Pak; Vassilina Nikoulina; Zhenisbek Assylbekov (ECAI, 2023)

Gradient descent fails to learn high-frequency functions and modular arithmetic. - Rustem Takhanov; Maxat Tezekbayev; Artur Pak; Arman Bolatov; Zhenisbek Assylbekov (Mach. Learn., 2025)

Learning Overspecified Gaussian Mixtures Exponentially Fast with the EM Algorithm. - Zhenisbek Assylbekov; Alan Legg; Artur Pak (CoRR, 2025)