Looking forward, the team aims to scale these models for larger, more complex datasets and explore further optimizations in quantum state encoding and quantum machine learning architecture design.

Approaches to quantum-enhanced machine learning. Quantum search In the mid-1990s, computer scientist Lov Grover showed that a future quantum computer can search an unsorted database – such as ...

The appeal of quantum machine learning lies in its potential to tackle problems that classical ML ... Honda Research Institute uses such data compression for image analysis using quantum computers.

For over a decade, researchers have considered boson sampling—a quantum computing protocol involving light particles—as a key ...

For 2023, she predicts that quantum algorithms have the potential to perform certain machine learning tasks faster and more accurately, especially for tasks such as image and speech recognition ...

shenzhen, May 20, 2025 (GLOBE NEWSWIRE) -- Shenzhen, May. 20, 2025/––MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), announced that quantum algorithms will be deeply integrated ...

Quantum mechanics, which is the study of the behavior of sub-atomic particles, provides a way to enhance the use of machine learning to resolve inherently complex problems around optimization ...

Quantum Machine Learning is an interdisciplinary field that harnesses the computational power of quantum systems to develop algorithms that can process and analyze data more efficiently than ...

image: This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms.