Improving conversion rate prediction via self-supervised pre-training in online advertising

no code implementations • 25 Jan 2024 • Alex Shtoff, Yohay Kaplan, Ariel Raviv

A major challenge in training models that predict conversions-given-clicks comes from data sparsity - clicks are rare, conversions attributed to clicks are even rarer.

Continual Learning

Audience Prospecting for Dynamic-Product-Ads in Native Advertising

no code implementations • 12 Dec 2023 • Eliran Abutbul, Yohay Kaplan, Naama Krasne, Oren Somekh, Or David, Omer Duvdevany, Evgeny Segal

One of the fastest growing segments of Gemini native is dynamic-product-ads (DPA), where major advertisers, such as Amazon and Walmart, provide catalogs with millions of products for the system to choose from and present to users.

Soft Frequency Capping for Improved Ad Click Prediction in Yahoo Gemini Native

no code implementations • 8 Dec 2023 • Michal Aharon, Yohay Kaplan, Rina Levy, Oren Somekh, Ayelet Blanc, Neetai Eshel, Avi Shahar, Assaf Singer, Alex Zlotnik

Yahoo's native advertising (also known as Gemini native) serves billions of ad impressions daily, reaching a yearly run-rate of many hundred of millions USD.

Collaborative Filtering

Unbiased Filtering Of Accidental Clicks in Verizon Media Native Advertising

no code implementations • 8 Dec 2023 • Yohay Kaplan, Naama Krasne, Alex Shtoff, Oren Somekh

However, we cannot ignore these positive events, as filtering these will cause the model to under predict.

Collaborative Filtering

Conversion-Based Dynamic-Creative-Optimization in Native Advertising

no code implementations • 13 Nov 2022 • Yohay Kaplan, Yair Koren, Alex Shtoff, Tomer Shadi, Oren Somekh

The predicted probabilities are then used in Gemini native auctions to determine which ads to present for every serving event (impression).

Attribute Collaborative Filtering