Efficient Clustering

Efficient clustering aims to group data points into meaningful clusters with minimal computational cost, addressing the challenges posed by increasingly large and complex datasets. Current research focuses on developing algorithms that leverage structural information (e.g., correlations between data points) to improve sample efficiency and scalability, exploring both novel clustering methods and enhancements to existing ones like k-means, often incorporating techniques such as graph-based approaches and the Minimum Description Length Principle for automatic parameter selection. These advancements are crucial for various applications, including protein analysis, large-scale ranking and selection, and personalized service delivery, enabling faster and more accurate insights from massive datasets.

Papers

April 24, 2024

Beyond ESM2: Graph-Enhanced Protein Sequence Modeling with Efficient Clustering
Shujian Jiao, Bingxuan Li, Lei Wang, Xiaojin Zhang, Wei Chen, Jiajie Peng, Zhongyu Wei
Protein Sequence Protein Language Model Efficient Clustering Protein Classification

February 3, 2024

"Clustering and Conquer" Procedures for Parallel Large-Scale Ranking and Selection
Zishi Zhang, Yijie Peng
Sample Complexity View Selection Correlation Clustering Efficient Clustering Cube and Conquer Parallel Clustering

December 19, 2023

Automatic Parameter Selection for Non-Redundant Clustering
Collin Leiber, Dominik Mautz, Claudia Plant, Christian Böhm
High Dimensional Parameter Selection Minimum Description Length Difference Subspace Efficient Clustering Multiple Clustering

November 22, 2023

A Joint Gradient and Loss Based Clustered Federated Learning Design
Licheng Lin, Mingzhe Chen, Zhaohui Yang, Yusen Wu, Yuchen Liu
Interest Loss Joint Optimization Local Model Clustered Federated Learning FL Algorithm Efficient Clustering

June 12, 2023

A Computational Theory and Semi-Supervised Algorithm for Clustering
Nassir Mohammad
Data Clustering Clustering Method Semi Supervised Clustering Efficient Clustering

June 7, 2023

Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion
Yash Bhalgat, Iro Laina, João F. Henriques, Andrew Zisserman, Andrea Vedaldi
Instance Segmentation Neural Field Representation Efficient Clustering Contrastive Factor Analysis Appropriate Contrastive Node Pair

December 30, 2022

Comparative Analysis of Clustering Techniques for Personalized Food Kit Distribution
Jude Francis, Rowan K Baby, Jacob Abraham, Ajmal P. S
Comparative Study Data Clustering Different Cluster Clustering Method Efficient Clustering

March 2, 2022

Efficient Dynamic Clustering: Capturing Patterns from Historical Cluster Evolution
Binbin Gu, Saeed Kargar, Faisal Nawab
High Efficiency Complex Pattern Clustering Method Clustering Result Dynamic Clustering Efficient Clustering

March 1, 2022

Belief propagation for supply networks: Efficient clustering of their factor graphs
Tim Ritmeester, Hildegard Meyer-Ortmanns
Supply Chain Belief Propagation Factor Graph Efficient Clustering

February 17, 2022

Recovering Unbalanced Communities in the Stochastic Block Model With Application to Clustering with a Faulty Oracle
Chandra Sekhar Mukherjee, Pan Peng, Jiapeng Zhang
Application Proficiency Community Detection Graph Clustering Cluster Structure Stochastic Block Model Test Oracle Efficient Clustering

December 29, 2021

A sampling-based approach for efficient clustering in large datasets
Georgios Exarchakis, Omar Oubari, Gregor Lenz
High Dimensional Data K Mean Large Datasets Efficient Clustering Sampling Based Approach

Efficient Clustering

Papers

Beyond ESM2: Graph-Enhanced Protein Sequence Modeling with Efficient Clustering

"Clustering and Conquer" Procedures for Parallel Large-Scale Ranking and Selection

Automatic Parameter Selection for Non-Redundant Clustering

A Joint Gradient and Loss Based Clustered Federated Learning Design

A Computational Theory and Semi-Supervised Algorithm for Clustering

Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion

Comparative Analysis of Clustering Techniques for Personalized Food Kit Distribution

Efficient Dynamic Clustering: Capturing Patterns from Historical Cluster Evolution

Belief propagation for supply networks: Efficient clustering of their factor graphs

Recovering Unbalanced Communities in the Stochastic Block Model With Application to Clustering with a Faulty Oracle

A sampling-based approach for efficient clustering in large datasets