Toma Sogabe, Associate Professor
i-PERC＆Department of Engineering Science
The University ofElectro-Communications
■Title: Opportunities and challenges for developing hybrid quantum-classical machine learning and optimization algorithms.
We present an overview of our progress on quantum-inspired and quantum-assisted algorithms for optimization and machine learning. We develop an end-to-end quantum-inspired support vector machine algorithm based on the deterministic Deutsch–Jozsa algorithm oracle. Meanwhile, we will introduce quantum neural networks-based machine learning and present quantified expressibility metrics as well as quantum regularization for different quantum ansatz. At last, we compare several popular quantum optimization algorithms including QAOA, QAA, VQE, and Qbsolv with classic algorithms such as Gurobi, and will discuss their advantages, limitations as well as challenges.
Kotaro Hasegawa Applied Research and Venture Team, Advantest Corporation
Micro LED technical trend and testing needs
MicroLED is a technology for future panel display. Even not reaching to major technology yet, there is many opportunities for the technology to replace existing display technologies. In this session, talk about market and technology trend, manufacturing workflow, issues on manufacturing and the testing needs/methodology to realize high quality products.