Research Blog

The framework achieves great coverage and performance across different incident triaging scenarios, and also outperforms other state-of-the-art root cause analysis methodologies.

A formal and interdisciplinary theory of learning and intelligence that combines biology, neuroscience, computer science, engineering and various branches of mathematics to provide a unifying framework, direction and a broader horizon for neural network and machine learning research.

Participating universities will structure listing data to help solve a real-world ecommerce challenge.

At eBay, we containerized Jenkins to provide a continuous build infrastructure on Kubernetes Clusters to power the ecommerce marketplace experience. Our goal was to leverage the capability of Kubernetes secrets, for managing the Jenkins credentials.

eBay researchers recently published a paper about a method for KG relation embedding using dihedral group. Experimental results on benchmark KGs show that the model outperforms existing bilinear form models and even deep learning methods.

Part of our mission within Core AI at eBay is to develop computer vision models that will power innovative and compelling customer experiences. But how can we compare several visual search models and say which of them works better? This article will describe a method that is tackling this problem directly from the eyes of the users.

Learn how eBay's architecture knowledge graph was developed; the benefits eBay has received from it; and the use cases we see now and in the future for this approach.

In this article, we propose a set of better practices, designed by and for eBay ML scientists, for facilitating weaving ML modeling into the cyclical Agile process flow.

Trade has played a critical role in the history of humanity and yet, data from ecommerce, the modern form of trading, has received limited attention from academia. We at eBay want to change that.