Workshop organized by:
F. Caruso
This workshop will cover the fascinating very interdisciplinary field of machine learning and its more recent generalization to quantum information. Recurrent networks, reinforcement learning, Boltzmann machines, deep learning, and neural networks will be discussed in various scientific fields and from both foundational and technological perspectives.
On one side, machine learning does very successfully solve very hard problems as detecting anomalous events in live streams of sensor data, self-driving cars, speech recognition, natural language, vision, playing games, trading strategies, etc.
On the other side, quantum information science also teems with excitement. By manipulating single particles at a subatomic level, one is able to perform Fourier transformation exponentially faster or search in a database quadratically faster than the classical limit. A future quantum computer will break the security of all the currently encrypted messages, and quantum cryptography already shows instead of an unbreakable tool to faithfully transmit information at a commercial level.
But, what can quantum computing contribute to machine learning? We naturally expect a speedup from quantum methods, but what kind of speedup?
We will bring together experts from quantum computing and machine learning to discuss the latest progress in the rapidly growing field of quantum machine learning.