Better Machine Learning When Data is Noisy and Incomplete Using Quantum Computers

D-Wave Systems had a presentation that summarized the utility of their quantum adiabatic system. It is a specialized QUBO solver. QUBO stands for quadratic unconstrained binary optimization and is a problem type traditionally used in computer science.

There is online documentation and training to understand how to use the D-Wave 2048 qubit system.

Probablistic Machine Learning

Most of the transformation that AI has brought to-date has been based on deterministic machine learning models such as feed-forward neural networks. The real world has a lot more uncertainty. Probabilistic models explicitly handle this uncertainty by accounting for gaps in our knowledge and errors in data sources.

Probabilistic modeling is a practical approach for designing machines that:

* Learn from noisy and unlabeled data
* Define confidence levels in predictions
* Allow decision making in the absence of complete information
* Infer missing data and latent correlations in data

D-Wave’s Quadrant’s algorithms enable accurate discriminative learning (predicting outputs from inputs) using less data by constructing generative models which jointly model both inputs and outputs. Quadrant offers the services of its in-house experts to help customers get the benefit of leading-edge machine learning solutions.

In May 2018, Quadrant announced working with Siemens Healthineers, a global leader in medical technology company. Siemens Healthineers and D-Wave took first place in the CATARACTS medical imaging grand challenge, using Quadrant’s generative machine learning algorithms to identify surgical instruments in videos with high accuracy. These algorithms are being researched as a way to improve patient outcomes through better augmented surgery and ultimately computer-assisted interventions (CAI).

“Machine learning has the potential to accelerate efficiency and innovation across virtually every industry. Quadrant’s models are able to perform deep learning using smaller amounts of labeled data, and our experts can help to choose and implement the best models, enabling more companies to tap into this powerful technology,” said Handol Kim, Sr. Director, Quadrant Machine Learning at D-Wave.


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