Applied Research.

Applied Research at Georgian Partners.

We take the latest technology and research trends and translate them into business solutions. Currently, we're looking at areas in advanced ML like transfer learning, representation learning and AutoML. We're also focused on technologies around trustworthy AI, including differential privacy, federated learning, fairness and bias detection, and transparency and explainability.

Why Applied Research?

We look at emerging technology areas within our thesis areas to find technologies that can help our portfolio companies to realize competitive advantages. The criteria we use to assess an applied research area include: ROI, scalability, speed and differentiation.

Tangible ROI

Select technology areas that can solve critical business problems.

Scalabilty

Select technology areas that can be applied to multiple internal and portfolio problems.

Speed

Decrease time to value by building expertise and applying it to multiple problems.

Differentiation

Create sustainable differentiation by de-risking innovation and research.

Papers.

Read through some of the papers that have been published by our applied research team. For more from the Impact team, be sure to check out the Georgian Impact Blog.

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Boosting Model Performance through Differentially Private Model Aggregation

Presented at the 13th Women in Machine Learning Workshop (WiML 2018) colocated with NeurIPS.

A Hybrid Instance-based Transfer Learning Method

Presented at Machine Learning for Health Workshop (ML4H) at NeurIPS 2018.

Privacy Versus Artificial Intelligence in Medicine

Published in Artificial Intelligence in Medicine, February 2019.