3 papers
cs.LG2026
Data-Native Global Optimization for Big Data K-means Clustering
Ravil Mussabayev, Rustam Mussabayev, Zukhra Yerdaliyeva +1
Big data clustering remains challenging: the Minimum Sum-of-Squares Clustering (MSSC) problem underlying K-means is NP-hard, and existing methods either reach poor local minima or…
cs.CL2026
MLLM-Microscope: Unlocking Hidden Structure Within Multimodal Large Language Models
Ravil Mussabayev, Rustam Mussabayev
This work presents MLLM-Microscope, a novel system designed for analyzing the hidden representations within Multimodal Large Language Models (MLLMs). Our system evaluates the linea…
cs.LG2024
Boosting K-means for Big Data by Fusing Data Streaming with Global Optimization
Ravil Mussabayev, Rustam Mussabayev
K-means clustering is a cornerstone of data mining, but its efficiency deteriorates when confronted with massive datasets. To address this limitation, we propose a novel heuristic…