Lectures related to String metric

Advanced Structure Discovery: Distance Metrics and Time Series Data

Explores clustering algorithms, distance metrics, and time series data analysis techniques.

Explores entity resolution techniques, data deduplication, similarity metrics, computational cost, blocking techniques, and scaling out similarity joins.

Temporality and Entity Resolution

Explores challenges in data temporality and techniques for entity resolution.

Distances and Motif Counts

Explores distances on graphs, cut norms, spanning trees, blockmodels, metrics, norms, and ERGMs in network data analysis.

Graph metrics: Statistical analysis

Explores graph metrics and statistical analysis in network clustering, including ERGMs application in sociology and asymptotics.

Ergodic properties of low complexity symbolic systems

Explores the influence of complexity on ergodic properties of symbolic systems, presenting the Curtis-Hedlund-Lyndon Theorem and constructions of minimal subshifts.

Data Summarization: Minhashing and Locality-Sensitive Hashing

Explores Jaccard similarity, minhashing, and locality-sensitive hashing for data summarization.

Data Compression: Privacy-Preserving Techniques

Explores privacy-preserving data management and data summarization techniques for finding similar items.

Supervised Learning: k-NN and Decision Trees

Introduces supervised learning with k-NN and decision trees, covering techniques, examples, and ensemble methods.

Cluster Analysis: Methods and Applications

Explores cluster analysis methods and applications in genomic data analysis, covering classification, gene expression clustering, visualization, distance metrics, and clustering algorithms.

The Impact Canvas: Using the Tool

Introduces the Impact Canvas tool for technology innovation in sustainable development.

KNN Classifier: Nearest Neighbor Approach

Explains the K-Nearest Neighbors classifier, assigning labels based on closest points and smoothing noise in labels.

Hyperbolic Functions: Tangent and Cotangent

Covers the definitions and examples of hyperbolic tangent and cotangent functions.

Privacy-preserving Data Management: Operations and Protocols

Explores privacy-preserving data management operations and summarization techniques for sensitive data protection.

Recommender Systems: Part 1

Introduces recommender systems, collaborative filtering, content-based recommendation, similarity metrics, and matrix factorization.

Recommender Systems: Overview and Methods

Explores the evolution of recommenders, collaborative filtering, Netflix Prize, model training, and optimization techniques.

Gaussian Naive Bayes & K-NN

Covers Gaussian Naive Bayes, K-nearest neighbors, and hyperparameter tuning in machine learning.

Link Prediction: Missing Edges and Probabilistic Methods

Explores link prediction in networks, covering missing edges, probabilistic methods, and causal inference challenges.

Recommender Systems: Basics and Techniques

Covers collaborative filtering and content-based methods for recommender systems, addressing cold start problems and making predictions.

Error Correction Codes: Basics

Introduces erasure and error channels, Hamming distance, and error correction codes.