Sept 18–23, 2022
Join NVIDIA at the 16th annual ACM Conference on Recommender Systems (RecSys 2022) to see how new research results, methods, libraries, and techniques in the broad field of recommender systems are driving our future. We’ll feature our own virtual theater with speakers from a variety of leading industries and domains, along with demos, related content, and more.
Conference Schedule at a Glance
At RecSys 2022, you can explore a range of groundbreaking work in the field of recommender systems. Take a closer look at the scheduled NVIDIA sessions that are part of this year’s program.
| Sunday 9/18 | Monday 9/19 | Tuesday 9/20 | Wednesday 9/21 | Thursday 9/22 | Friday 9/23 |
|---|---|---|---|---|---|
| Training and Deploying Multi-Stage Recommender Systems (Tutorial) 8:30 - 11:00 a.m. PST |
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| NVIDIA Meet-up (Virtual and In-Person) Merlin HugeCTR: GPU-accelerated Recommender System Training and Inference (Industry Poster) 10:30 - 11:00 a.m. PST |
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| A GPU-specialized Inference Parameter Server for Large-Scale DeepRecommendation Models (Industry Talk and Paper) 2:00 - 3:30 p.m. PST |
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| Building and Deploying a Multi-Stage Recommender System with Merlin (Demo) 6:00 p.m. PST |
A Diverse Models Ensemble for Fashion Session-Based Recommendation (Talk and Paper) 4:30 - 4:42 p.m. PST |
Don’t miss a session. Register now for RecSys 2022.
Virtual Theater
Hear from industry leaders, data scientists, and engineers as they explain their groundbreaking work for building, training, optimizing, and deploying recommender systems.
Top Recommender System Resources
NVIDIA Merlin
Learn about NVIDIA Merlin™, an open source framework for building recommender systems. Merlin empowers data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale.
Hierarchical Parameter Server (HPS)
In this ACM RecSys 2022 accepted paper, discover how HPS combines a high performance GPU embeddings cache with an hierarchical storage architecture to realize low-latency retrieval of embeddings for online model inference.
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.
Multi-Stage Recommender Systems Tutorial
Attend this hands-on ACM RecSys 2022 Tutorial and 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.
GPU Accelerated Recommender Systems Training and Inference
In this ACM RecSys 2022 accepted submission, learn about NVIDIA Merlin HugeCTR, a framework for click through rate estimation that is optimized for training and inference. It also enables training at scale with model-parallel embeddings and data-parallel neural networks.
Reduce Model Development Friction
With the Merlin Models library, access common architectures that can be coupled with different prediction tasks, loss functions, and negative sampling strategies to ease development and deployment.
Exploring Production Ready Recommenders
Deploying custom models to production is a challenge. Explore potential ways to ease deployment with Merlin Systems in this blog post.
NVIDIA Recommender Summit 2022
During this NVIDIA AI online event, join fellow data scientists and engineers from Netflix, Twitter, NVIDIA, and more to discuss learnings and best practices on building and deploying effective recommender systems.
Scale Faster with Two Tower and Merlin
Introduction to popular Two Tower architecture, why it solves for challenges associated with candidate retrieval, and how using Merlin Models enables training with 4 lines of code.
Sequential and Session-Based Recommendation
In this blog, we cover sequential and session-based recommendation tasks, including why it’s important and practical use cases. We also provide a brief overview of our Transformers4Rec solution.
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.
NVIDIA GTC Keynote
Watch NVIDIA CEO Jensen Huang discuss the importance of AI frameworks, including NVIDIA Merlin™, in the NVIDIA GTC keynote.
Large-scale Recommender System Inference
Serving user requests with low latency and high accuracy is critical for recommender systems. NVIDIA Merlin introduces HPS, a scalable solution with multilevel adaptive storage to enable deployment of Terabyte-size models under real-time latency constraints!
Training Terabyte-scale Recommenders with Ease
In this post, learn how NVIDIA Merlin Distributed Embeddings enables developers to rapidly train Terabyte-scale embedding based models in TensorFlow 2 with just a few lines of code!
NVIDIA Wins RecSys Challenges
Industry challenges help advance the recommender system field for everyone. NVIDIA’s wins are fueling ideas for new techniques into recsys frameworks like NVIDIA Merlin.
Recommender Systems Best Practices
Read about the latest trends for recommender system practices within industry. The whitepaper includes insights from industry leads from companies such as Tencent, Meituan, Wayfair, Magazine Luiza, The New York Times, and more.
The Developer Conference for the Era of AI and the Metaverse
Join us this September for a GTC that will inspire your next big idea. This is a don't miss opportunity to learn from experts and leaders in their fields on how AI is transforming industries and profoundly impacting the world. It all happens online 19-22.
NVIDIA Deep Learning Institute (DLI)
Get Technical Training at GTC, September 19-22, 2022
The NVIDIA Deep Learning Institute (DLI) is offering a variety of hands-on full-day workshops and training labs covering AI, accelerated computing, and data science at GTC, September 19-22, 2022.
During the workshops, you’ll get access to a fully configured, GPU-accelerated server in the cloud, gain practical skills for your work, and even earn a certificate of subject matter competency. The 2-hour training labs are included in the free GTC conference pass.
Popular Training Labs
Training and Deploying Multi-Stage Recommender Systems
Accelerating and Scaling Inference with NVIDIA GPUs
Introduction to Graph Neutral Networks
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