Outlier-Robust Clustering of Gaussians and Other Non-Spherical Mixtures
Explore robust clustering techniques for Gaussian mixtures and non-spherical distributions, covering TV-separation, anti-concentration, and sum-of-squares relaxation methods.
Beyond the Blacklists - Detecting Malicious URL Through Machine Learning
Explore machine learning techniques for detecting malicious URLs beyond traditional blacklists, focusing on HTTP-based communications and behavioral modeling for improved malware detection.
CloudCluster - Unearthing the Functional Structure of a Cloud Service
Unearths cloud service functional structure using VM-to-VM traffic matrix clustering. Aids management by revealing design patterns, enabling cost reduction, and identifying anomalies and misconfigurations.
Evaluation and Refinement of Clustered Search Results with the Crowd
Innovative approach using crowdsourcing to evaluate and improve clustered search results, enhancing user exploration and discovery in large result sets.
Proving and Disproving Equivalence of Functional Programming Assignments
Explore an automated approach for verifying programming assignments using equivalence checking, functional induction, and clustering algorithms. Learn how to prove correctness and provide counterexamples efficiently.
Analysis of SARS-CoV-2 Sequencing Data
Explore advanced techniques for analyzing SARS-CoV-2 sequencing data, including haplotype assembly, phylogeny reconstruction, variant identification, and network representation of genomic information.
Methods for Disease Analysis Using Multiomic Data
Explore advanced methods for analyzing diseases using multiomic data, focusing on clustering algorithms, cancer subtyping, and driver gene prioritization.
Exploring Clustering Algorithms in Machine Learning
Dive into clustering algorithms, exploring principles and real-world applications. Learn various types, including K-means, and understand how to implement and evaluate them effectively.
New Directions in Correlation Clustering and Biclustering
Explore advanced techniques in correlation clustering and biclustering, focusing on novel approaches and applications in data analysis and machine learning.
On Clustering scRNA-seq Data
Explore challenges and strategies in clustering single-cell RNA sequencing data, focusing on the k-cluster method's effectiveness for analyzing neuronal datasets in fruit flies.
Agrupamentos Explicáveis e Agrupamentos Hierárquicos
Explore os fundamentos teóricos e práticos de agrupamentos explicáveis e hierárquicos, abordando técnicas probabilísticas e métodos de ligação para análise eficiente de dados e computação.
K-means Clustering and Validation Methods in Data Mining - Spring 2023
Master clustering algorithms through k-means, k-medoids, and Lloyd's algorithm, including initialization techniques, validation methods, and performance metrics for effective data mining applications.
Classic Problems with Modern Techniques - Prize-collecting Framework
Explore state-of-the-art approximation algorithms for classic network design problems using modern techniques, from clustering to recursive methodologies.