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Poland’s Tech Talents Found a Method for Improving Neural Networks’ Performance.

RTB House, a global company that provides retargeting technology, has devised an innovative approach to building neural network architecture: It improves the way machines predict conversion value. This results in advertising campaigns bringing in ROIs. The novel concept will be presented during the upcoming 2017 International Joint Conference on Neural Networks in Anchorage, Alaska. It will be the third conference, after the 33rd International Conference on Machine Learning (ICML 2016) in New York City and the 31st AAAI Conference on Artificial Intelligence (AAAI 2017) in San Francisco, where RTB House findings in the field of artificial intelligence have been presented.

Neural Networks are biologically-inspired programming models which enable a computer to learn from observational data – similar to the way a human brain learns from perception. It is one of the most powerful tools when it comes to solving digital classification problems, used widely in industries for recognition in videos, image, speech, language, DNA or even stock markets and the weather.

Unfortunately for the marketing industry, a neural network is limited in its ability to predict continuous values, for example, figures like order value or daily revenues.

RTB House developed an innovative method that makes it possible to derive more precise and reliable estimations of desired value. It can be used to enhance any neural network trained to solve value estimation tasks.

Bartek Romański, Chief Technology Officer RTB House (pictured top left) remarks, “Neural networks, especially deep learning architectures, have become the new standard in making sense of the digital world and leveraging the enormous opportunities within data. AI has forever changed the way we do digital advertising. Google and Facebook have been training brain-inspired neural networks to better represent the real world, and classify, cluster and predict outcomes in data. Today, deep learning is finding its way into uses across every industry, from healthcare, to e-commerce, self-driving cars and even art. We are extremely proud to be a contributor to the field of deep learning in advertising.”

Konrad Żołna, Research Scientist at RTB House, explains that how the model works to find optimized values in conversions: “Our method extends the training phase of the conversion value model with carefully constructed additional targets, making the final model’s predictions more robust and precise. In practice, it means that our self-learning algorithms are able to ultra-precisely identify buyers with the largest potential basket value, and then display a personalized message encourage them to finalize the transaction.”