Clustering Performance

Clustering performance, the effectiveness of algorithms in grouping similar data points, is a central problem in unsupervised machine learning, aiming to improve accuracy, efficiency, and scalability. Recent research focuses on enhancing clustering through techniques like active learning (strategically querying human input), leveraging graph structures and node attributes for improved community detection, and integrating representation learning (e.g., contrastive learning) to handle high-dimensional data. These advancements are significant for various applications, including data analysis, image segmentation, and operational decision-making, where efficient and accurate clustering is crucial for extracting meaningful insights from complex datasets.

Papers

July 14, 2024

A3S: A General Active Clustering Method with Pairwise Constraints
Xun Deng, Junlong Liu, Han Zhong, Fuli Feng, Chen Shen, Xiangnan He, Jieping Ye, Zheng Wang
Semi Supervised Clustering Clustering Performance Adaptive Clustering Clustering Based Active Learning Pairwise Constraint Adaptive Aggregation

July 9, 2024

Modularity aided consistent attributed graph clustering via coarsening
Samarth Bhatia, Yukti Makhija, Manoj Kumar, Sandeep Kumar
Graph Drawing Graph Clustering Modularity Function Variational Graph Clustering Performance Modularity Maximization

January 12, 2024

CCFC: Bridging Federated Clustering and Contrastive Learning
Jie Yan, Jing Liu, Zhong-Yuan Zhang
Contrastive Learning Clustering Friendly Representation Federated Clustering Clustering Performance

December 12, 2023

Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization
Jiyoung Kim, Kyuhong Shim, Insu Lee, Byonghyo Shim
Semantic Segmentation Unsupervised Setting Unsupervised Semantic Segmentation Prompt Expansion High Dimensional Space Product Quantization Clustering Performance

December 2, 2023

A ripple in time: a discontinuity in American history
Alexander Kolpakov, Igor Rivin
Pre Trained Time Matter Ticket BERT Historical Text Clustering Performance Vector Embeddings Inherent Discontinuity NLP Classification Task

November 29, 2023

Mostly Beneficial Clustering: Aggregating Data for Operational Decision Making
Chengzhang Li, Zhenkang Peng, Ying Rong
Raw Data Decision Making Data Aggregation Aggregation Method Clustering Performance Two Stage Aggregation

September 7, 2023

Privacy-preserving Continual Federated Clustering via Adaptive Resonance Theory
Naoki Masuyama, Yusuke Nojima, Yuichiro Toda, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota
Clustering Algorithm Federated Clustering Clustering Performance Adaptive Resonance

June 7, 2023

Towards High-Performance Exploratory Data Analysis (EDA) Via Stable Equilibrium Point
Yuxuan Song, Yongyu Wang
Large Scale Datasets Data Visualization Exploratory Data Analysis Clustering Performance Visualization Method Equilibrium Point Transportation Typology

April 30, 2023

Time series clustering based on prediction accuracy of global forecasting models
Ángel López Oriona, Pablo Montero Manso, José Antonio Vilar Fernández
Prediction Accuracy Time Series Clustering Global Forecasting Clustering Performance Model Based Clustering Divisive Hierarchical Clustering Algorithm

March 3, 2023

Contrastive Hierarchical Clustering
Michał Znaleźniak, Przemysław Rola, Patryk Kaszuba, Jacek Tabor, Marek Śmieja
Hierarchical Clustering Contrastive Example Contrastive Clustering Clustering Performance

January 7, 2023

k-Means SubClustering: A Differentially Private Algorithm with Improved Clustering Quality
Devvrat Joshi, Janvi Thakkar
Differential Privacy K Mean Private Data Private Algorithm Exponential Mechanism Private Clustering Clustering Performance

November 22, 2022

Scalable and Effective Conductance-based Graph Clustering
Longlong Lin, Rong-Hua Li, Tao Jia
Potential Scalability Graph Clustering Clustering Performance

November 19, 2022

EGRC-Net: Embedding-induced Graph Refinement Clustering Network
Zhihao Peng, Hui Liu, Yuheng Jia, Junhui Hou
Graph Structure Clustering Performance

October 6, 2022

TensorAnalyzer: Identification of Urban Patterns in Big Cities using Non-Negative Tensor Factorization
Jaqueline Silveira, Germain García, Afonso Paiva, Marcelo Nery, Sergio Adorno, Luis Gustavo Nonato
Person Identification Urban Environment Tensor Decomposition Temporal Correlation Clustering Algorithm Tensor Data Clustering Performance Urban Pattern Nonnegative Tensor Factorization

August 2, 2022

Late Fusion Multi-view Clustering via Global and Local Alignment Maximization
Siwei Wang, Xinwang Liu, En Zhu
Multi View World Event Data Clustering Optimal Alignment Clustering Performance

July 8, 2022

Few-Example Clustering via Contrastive Learning
Minguk Jang, Sae-Young Chung
Contrastive Learning Clustering Performance Cluster Assignment

June 9, 2022

Unsupervised Deep Discriminant Analysis Based Clustering
Jinyu Cai, Wenzhong Guo, Jicong Fan
Deep Neural Network Latent Space Unsupervised Manner Unsupervised Deep Learning Clustering Performance

May 12, 2022

Ensemble Clustering via Co-association Matrix Self-enhancement
Yuheng Jia, Sirui Tao, Ran Wang, Yongheng Wang
Feature Enhancement Clustering Result Clustering Performance Affinity Matrix Ensemble Clustering

February 3, 2022

Fast and explainable clustering based on sorting
Xinye Chen, Stefan Güttel
Different Cluster Explainable Clustering Clustering Performance Cluster Shape