Knowledge Inference for Graphs

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Related lectures (55)

Graph Theory Basics Log in to Mediaspace to watch this video

Introduces graph theory basics, Ramsey theory, and graph coloring concepts.

Graph Machine Learning Log in to Mediaspace to watch this video

Delves into graph-enhanced machine learning, focusing on fraud detection, malware detection, and recommendation systems.

Graph Algorithms: Modeling and Representation Log in to Mediaspace to watch this video

Covers the basics of graph algorithms, focusing on modeling and representation of graphs in memory.

Information Extraction: Bootstrapping Log in to Mediaspace to watch this video

Explores Information Extraction approaches like hand-written patterns and distant supervision, with examples of entity pairs matching patterns.

Machine Learning and Modern AI: SWOT Analysis Log in to Mediaspace to watch this video

Covers a SWOT analysis of Machine Learning and Artificial Intelligence, exploring strengths, weaknesses, opportunities, and threats in the field.

Document Analysis: Topic Modeling Log in to Mediaspace to watch this video

Explores document analysis, topic modeling, and generative models for data generation in machine learning.

Machine Learning at the Atomic Scale Log in to Mediaspace to watch this video

Explores simple models, electronic structure evaluation, and machine learning at the atomic scale.

Semi-Definite Programming Log in to Mediaspace to watch this video

Covers semi-definite programming and optimization over positive semidefinite cones.

Graph Surfaces and Sphere in Spherical Coordinates Log in to Mediaspace to watch this video

Covers graph surfaces with an example of a surface defined by a parametric equation.

Supervised Learning Fundamentals Log in to Mediaspace to watch this video

Introduces the fundamentals of supervised learning, including loss functions and probability distributions.

Proximal Gradient Descent: Optimization Techniques in Machine Learning Log in to Mediaspace to watch this video

Discusses proximal gradient descent and its applications in optimizing machine learning algorithms.

Introduction to Data Science Log in to Mediaspace to watch this video

Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.

Logistic Regression: Classification Log in to Mediaspace to watch this video

Covers supervised learning, classification using logistic regression, and challenges in optimization.

Learning-aided Program Reasoning Log in to Mediaspace to watch this video

Explores bug-finding, verification, and the use of learning-aided approaches in program reasoning, showcasing examples like the Heartbleed bug and differential Bayesian reasoning.

Optimization Principles Log in to Mediaspace to watch this video

Covers optimization principles, including linear optimization, networks, and concrete research examples in transportation.

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