2024年2月20日 · Machine Learning. Machine learning uses data to teach AI systems to imitate the way that humans learn. They can find the signal in the noise of big data, helping businesses improve their operations. We've been in the field since since the beginning: IBMer Arthur Samuel even coined the term “Machine Learning” back in 1959. Our work

2021年7月12日 · Quantum Machine Learning. We now know that quantum computers have the potential to boost the performance of machine learning systems, and may eventually power efforts in fields from drug discovery to fraud detection. We're doing foundational research in quantum ML to power tomorrow’s smart quantum algorithms. Our work

Nonetheless, there are other fields like machine learning, finance, or chemistry where quantum computation could be useful with current quantum devices. This manuscript aims to present a review of the literature published between 2017 and 2023 to identify, analyze, and classify the different types of algorithms used in quantum machine learning ...

These quantum improvements either try to improve over classical algorithms or consider quantum learning when the data itself could be presented in a quantum manner. In this talk, I will look at a few specific problems/computational models for which quantum algorithms provide a speedup to machine learning tasks in a rigorous manner.

The intent of this workshop is to bring together researchers, practitioners, and scientific communities to discuss methods that utilize extreme scale systems for learning graph data. This workshop will focus on the greatest challenges in utilizing high-performance computing (HPC) for machine learning with graphs and methods for exploiting ...

2025年1月29日 · International Conference on Machine Learning. ... ICLR 2024. 48. International Conference on Learning ...

Aim a firehose of data at a human, and you get information overload. But if you do the same to a computer, you get machine-learning models that can learn to complete sentences as you type or detect tumors in medical scans that are often too subtle for a human eye to see.

2021年10月12日 · Neuro-symbolic AI. We see Neuro-symbolic AI as a pathway to achieve artificial general intelligence. By augmenting and combining the strengths of statistical AI, like machine learning, with the capabilities of human-like symbolic knowledge and reasoning, we're aiming to create a revolution in AI, rather than an evolution.

2022年8月24日 · In vertical federated learning, the data are complementary; movie and book reviews, for example, are combined to predict someone’s music preferences. Finally, in federated transfer learning, a pre-trained foundation model designed to perform one task, like detecting cars, is trained on another dataset to do something else, like identify cats.

The recent wave of using machine learning to analyze and manipulate real-world systems has inspired many research topics in the joint interface of machine learning and dynamical systems. However, the real world applications are diverse and complex with vulnerabilities such as simulation divergence or violation of certain prior knowledge.