Srishti Saha
High Dimension Data Analysis - A tutorial and review for Dimensionality Reduction Techniques
High Dimension Data Analysis - A tutorial and review for Dimensionality Reduction Techniques
This article explains and provides a comparative study of a few techniques for dimensionality reduction. It dives into the mathematical explanation of several feature selection and feature transformation techniques, while also providing the algorithmic representation and implementation of some other techniques. Lastly, it also provides a very brief review of various other works done in this space.
29 points
0 issues
The use of Mathpix OCR with EDICO scientific editor to help blind Students in STEM education
The use of Mathpix OCR with EDICO scientific editor to help blind Students in STEM education
In this tutorial we'll show how Mathpix OCR is helpful to instantly transpose math and science assignments both in braille and speech. We'll use the free EDICO Scientific Editor to demonstrate how a math assignment can be imported using Mathpix technology, and how it can be solved using a Refreshable Braille Display.
5 points
0 issues
David McCaffary
Towards continual task learning in artificial neural networks
Towards continual task learning in artificial neural networks
Critical appraisal of prominent current approaches to alleviating catastrophic forgetting in neural networks, drawing on inspiration from neuroscience.
5 points
0 issues
Event Camera: the Next Generation of Visual Perception System
Event Camera: the Next Generation of Visual Perception System
Event camera can extend computer vision to scenarios where it is currently incompetent. In the following decades, it is hopeful that event cameras will be mature enough to be mass-produced, to have dedicated algorithms, and to show up in widely-used products.
29 points
0 issues
Adversarial Learning on Graph
Adversarial Learning on Graph
This review gives an introduction to Adversarial Machine Learning on graph-structured data, including several recent papers and research ideas in this field. This review is based on our paper “A Survey of Adversarial Learning on Graph”.
5 points
0 issues
Probing The Full Monty Hall Problem
Probing The Full Monty Hall Problem
A tutorial on the Monty Hall problem in statistics.
7 points
0 issues
Emil Junker
Manipulative Attacks in Group Identification
Manipulative Attacks in Group Identification
This review provides an introduction to the group identification problem and gives an overview of the feasibility and computational complexity of manipulative attacks in group identification.
2 points
0 issues
Group Equivariant Convolutional Networks in Medical Image Analysis
Group Equivariant Convolutional Networks in Medical Image Analysis
This is a brief review of G-CNNs' applications in medical image analysis, including fundamental knowledge of group equivariant convolutional networks, and applications in medical images' classification and segmentation.
8 points
0 issues
A Review of Trustworthy Graph Learning
A Review of Trustworthy Graph Learning
In this review, we will explore how to develop trustworthy graph neural networks (GNNs) models from different aspects.
26 points
0 issues
Co-Tuning: An easy but effective trick to improve transfer learning
Co-Tuning: An easy but effective trick to improve transfer learning
Transfer learning is a popular method in the deep learning community, but it is usually implemented naively (eg. copying weights as initialization). Co-Tuning is a recently proposed technique to improve transfer learning that is easy to implement, and effective to a wide variety of tasks.
4 points
0 issues
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