Résumé
In recent years, many quantum machine learning algorithms have been proposed that can potentially offer significant speedup over corresponding classical algorithms. In this talk, we will discuss what is needed for a full-scale, fault-tolerant, quantum computer to implement these algorithms. We will also present recent quantum circuits for automatic clustering (k-means, spectral clustering) and neural networks (fully connected, convolutional, orthogonal).
