Displaying 338 resources
Transfer Learning
This lecture overviews Transfer Learning (TL) that has many applications in DNN training and adaptation, Image Understanding, Text Mining, Activity Recognition, Bioinformatics, Transportation.
Graph Convolutional Networks
This lecture overviews Graph Convolutional Networks (GCN) that have many applications in Deep Learning, Signal and Video Analysis, Network Theory, Web Science and Social Media Analytics. It covers the following topics in detail: Graph Convolutions.
Data Clustering
This lecture overviews Data Clustering that has many applications in e.g., facial image clustering, signal/image clustering, concept creation. It covers the following topics in detail: Clustering Definitions.
Robust Statistics
This lecture overviews Robust Statistics that has many applications in Data Analytics and Digital Signal Processing and Analysis. It covers the following topics in detail: Outliers.
AI4Media Workshop on GANs for Media Content Generation
Generative Adversarial Networks (GANs) are part of the cutting edge in recent machine learning research.
A comprehensive survey of geometric deep learning
The survey provides a comprehensive overview of deep learning methods for geometric data (point clouds, voxels, network graphs etc.). The relevant knowledge and theoretical background of geometric deep learning is presented first.
Dynastic Potential Crossover Operator
An optimal recombination operator for two-parent solutions provides the best solution among those that take the value for each variable from one of the parents (gene transmission property).
Introduction to 2D Computer Vision
This lecture overviews digital images and 2D Computer Vision (image analysis).
Graph Neural Networks
This lecture overviews Graph Neural Networks that has many applications in Deep Learning, Signal and Video Analysis, Network Theory, Web Science and Social Media Analytics. It covers the following topics in detail: Introduction to Graphs.
AI and Computational Politics
The aim of this lecture is to a) define Computational Politics as a discipline lying at the intersection of Political science and Computer science and b) present the use of AI and IT tools in political data analysis.
Computational Politics has vario
Gray Box Optimization
In Gray Box Optimization, the optimizer is given access to the set of M subfunctions. We prove Gray Box Optimization can efficiently compute hyperplane averages to solve non-deceptive problems in time.