www.cs.cmu.edu

John Wieting

I am a PhD student at Carnegie Mellon University supervised by Taylor Berg-Kirkpatrick and Graham Neubig. I also collaborate with Kevin Gimpel at the Toyota Technological Institute at the University ...
Frontiers

Multiclass classification using quantum convolutional neural networks with hybrid quantum-classical learning

Multiclass classification is of great interest for various applications, for example, it is a common task in computer vision, where one needs to categorize an image into three or more classes. Here we ...
Frontiers

Development of a Machine Learning Classifier for Brain Tumors Diagnosis Based on DNA Methylation Profile

Background: More than 150 types of brain tumors have been documented. Accurate diagnosis is important for making appropriate therapeutic decisions in treating the diseases. The goal of this study is ...
Scientific Research Publishing

Basic Tenets of Classification Algorithms K-Nearest-Neighbor, Support Vector Machine, Random Forest and Neural Network: A Review ()

1 Department of Basic Sciences, School of Basic and Biomedical Sciences, University of Health and Allied Sciences, Ho, Ghana. 2 Department of Statistics and Actuarial Science, University of Ghana, ...
Ars Technica

How neural networks work—and why they’ve become a big business

The last decade has seen remarkable improvements in the ability of computers to understand the world around them. Photo software automatically recognizes people’s faces. Smartphones transcribe spoken ...
Hacker

Deep Learning: Feedforward Neural Networks Explained

Your browser does not support the audio element. Feedforward neural networks are also known as Multi-layered Network of Neurons (MLN). These networks of models are ...