Existing explanation models generate only text for recommendations but still struggle to produce diverse contents. In this paper, to further enrich explanations, we propose a new task named personalized showcases, in which we provide both textual and...
In this article About ads on Google About ads on partner sites and apps Turn on or off personalized ads Control data saved from partner sites to your Google Account About ads on Google As you use …
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In federated learning, model personalization can be a very effective strategy to deal with heterogeneous training data across clients. We introduce WAFFLE (Weighted Averaging For Federated LEarning), a personalized collaborative machine learning algo...
In recent years, Federated Learning (FL) has shown significant advancements in its ability to perform various natural language processing (NLP) tasks. This work focuses on applying personalized FL for on-device language modeling. Due to limitations o...
Personalized genomics is the human genetics-derived study of analyzing and interpreting individualized genetic information by genome sequencing to identify
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Personalized image synthesis has emerged as a pivotal application in text-to-image generation, enabling the creation of images featuring specific subjects in diverse contexts. While diffusion models have dominated this domain, auto-regressive models,...
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approaches to personalizing search results, involving modifying the user's query and re-ranking search results. Google introduced personalized search in 2004
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huge level. Personalized children's storybooks—wherein the child becomes the protagonist, with the name and image of the child personalized—are extremely
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We study the problem of personalized advertisement recommendation (PAR), which consist of a user visiting a system (website) and the system displaying one of $K$ ads to the user. The system uses an internal ad recommendation policy to map the user's...
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This paper proposes a novel approach for constructing effective personalized policies when the observed data lacks counter-factual information, is biased and possesses many features. The approach is applicable in a wide variety of settings from healt...
We present an approach to automatically generate interfaces supporting personalized interaction with digital libraries; these interfaces augment the user-DL dialog by empowering the user to (optionally) supply out-of-turn information during an inte...
It remains unknown whether personalized recommendations increase or decrease the diversity of content people consume. We present results from a randomized field experiment on Spotify testing the effect of personalized recommendations on consumption d...