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The Machine Learning Center at Georgia Tech (ML@GT) invites you to attend a seminar discussing the challenges of machine learning at Google Ads with Google software engineers Kazoo Sone and Pradyumna Narayana. The event will be held virtually via Bluejeans Events and is open to the public. Registration is required.
TALK TITLE
Machine Learning Challenges at Google Ads
ABSTRACT
While we have made significant advances in the last two decades, serving the most relevant ads to our users is still a big challenge to date. In particular, commercial contents are full of images, videos in addition to textual information, and understanding our advertiser products and offers from their ad creatives and landing pages poses interesting multimodal modeling problems. In this talk, we will discuss a new multimodal task (Multi-Image Summarization) and the associated dataset we are releasing. We will also talk about our recent work which co-embeds text and image in a shared embedding space to improve a cross-modal retrieval task. Then we will share some challenges & experiences from quality improvements in Search Ads products.
ABOUT PRADYUMNA
Pradyumna Narayana is a software engineer for Google. He joined Google in 2018 and is conducting research at the intersection of computer vision and natural language processing for Search Ads. He earned his PhD in the area of Computer Vision from Colorado State University in 2018. His Ph.D work focused on Gesture recognition from videos using Deep Learning. Prior to that, he earned his MS from Colorado State University in 2015.
ABOUT KAZOO
Kazoo Sone is a software engineer for Google. Since he joined Google in 2011, he has led several machine learning & natural language processing projects for Search Ads and Research and contributed to many of Google’s Ads products. He earned his MS from Georgia Tech and Ph.D from Caltech.
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