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NVIDIA at RecSys 2022 and GTC 2022 Event Recap

Explore the latest NVIDIA demos, technical content, and more from RecSys 2022 and GTC 2022.


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Explore the latest NVIDIA demos, technical content, and more from RecSys 2022 and GTC 2022.
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Event Recap
NVIDIA at RecSys 2022 and GTC 2022.
Must-See Resources from RecSys 2022 and GTC 2022.
Explore our latest recommender system videos, papers, and blogs.
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GTC 2022 AI Workflows Keynote Recap
Explore the latest updates and announcements for the most powerful AI workflows from NVIDIA, including NVIDIA Merlin, and find new ways to put AI into production.


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Multi-Stage Recommender Systems Tutorial
In this ACM RecSys 2022 accepted paper, dive into how to make developing and deploying recommender systems easier. Covers methods for evaluating existing approaches, developing new ideas, and deploying them to production.

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Hierarchical Parameter Server (HPS)
In this ACM RecSys 2022 accepted paper, discover how HPS combines a high-performance GPU embeddings cache with a hierarchical storage architecture to realize low-latency retrieval of embeddings for online model inference.

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Models Ensemble for Fashion Session-Based Recommendation
This year’s RecSys Challenge, organized by Dressipi, was focused on the session-based recommendation problem for the fashion e-commerce domain. In this paper, the NVIDIA team presents its solution that placed third in the challenge.

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Recommender System Training and Inference
In this ACM RecSys 2022 accepted submission, learn about NVIDIA Merlin HugeCTR, a framework for click-through-rate estimation that’s optimized for training and inference. It also enables training at scale with model-parallel embeddings and data-parallel neural networks.

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Multi-Stage Recommender Systems Demo
In this ACM RecSys 2022 accepted submission, watch a technical walk through implementation of the four stages of recommender systems.




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GTC 2022 Keynote

Watch NVIDIA CEO Jensen Huang discuss the importance of AI frameworks, including NVIDIA Merlin, in the NVIDIA GTC keynote.


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Recommender Systems, Not Just Recommender Models
Read about a four-stage design pattern that builds understanding and consensus about what recommender systems (not just models) look like in production.

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