Lectures related to Taxonomy Induction: Relations Extraction and Graph Construction

Covers graph properties, representations, and traversal algorithms using BFS and DFS.

Automorphism Groups: Trees and Graphs III

Explores automorphism groups of trees and graphs, including actions on trees and group homomorphisms.

Graphs in Deep Learning: Applications and Techniques

Explores the role of graphs in deep learning, focusing on their structure, applications, and techniques for processing graph data.

Semantic Web & Information Extraction

Explores Semantic Web, ontologies, information extraction, key phrases, named entities, and knowledge bases.

Graph Algorithms: Modeling and Traversal

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

Real Functions: Graphs and Properties

Explores real functions, their graphs, properties, and transformations, including symmetry and surjection.

Information Extraction: Algorithms and Techniques

Explores algorithms and techniques for information extraction, including Viterbi algorithm, named entities recognition, and distant supervision.

Graphical Models: Representing Probabilistic Distributions

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.

Information Extraction: Methods and Applications

Explores methods for information extraction, including traditional and embedding-based approaches, supervised learning, distant supervision, and taxonomy induction.

Automorphism groups: Trees and Graphs

Explores automorphism groups in trees and graphs, focusing on ends and types of automorphisms.

Partial Derivatives: Understanding Tangents

Explores partial derivatives and their role in determining tangents to graphs.

General Mathematics I: Derivatives and Tangents

Explores derivatives, tangents, and elementary function rules in general mathematics.

Digital Humanities Lab: Practices

Introduces students to digital humanities through practical exercises, such as working on a large ongoing project.

Information Extraction & Knowledge Inference

Explores information extraction, knowledge inference, taxonomy induction, and entity disambiguation.

Mathematical Analysis: Functions and Composition

Covers the analysis of functions, composition, and mathematical induction.

Information Extraction: Approaches and Techniques

Covers Information Extraction approaches, including hand-written patterns and supervised learning.

Entity & Information Extraction

Explores knowledge extraction from text, covering key concepts like keyphrase extraction and named entity recognition.

Automorphism groups of trees and graphs

Explores automorphisms of graphs, focusing on automorphism groups, Cayley-Abels graphs, and quasi-isometry.

Convex Functions

Covers the properties and operations of convex functions.

Harmonic Oscillations: Graphs

Explores the construction of graphs for harmonic oscillations with different amplitudes and phases.