Apple is sponsoring the Neural Information Processing Systems Conference (NeurIPS), which will be held in New Orleans, Louisiana from November 28 to December 9. NeurIPS is a global conference focused on fostering the exchange of research on neural information processing systems in their biological, technological, mathematical, and theoretical aspects.

Schedule

Below is the schedule of Apple sponsored workshops and events. Check back for our accepted paper presentation times and locations. Visit the NeurIPS 2022 website for the full conference schedule.

Monday November 28

Tuesday November 29

Wednesday November 30

Thursday December 1

Friday December 2

Saturday December 3

Monday December 5

Accepted Papers

Conference Accepted Papers

FLAIR: Federated Learning Annotated Image Repository

Congzheng Song, Filip Granqvist, Kunal Talwar

GAUDI: A Neural Architect for Immersive 3D Scene Generation

Miguel Angel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Joshua Susskind

Learning to Break the Loop: Analyzing and Mitigating Repetitions for Neural Text Generation

Jin Xu, Xiaojiang Liu, Jianhao Yan, Deng Cai, Huayang Li, Jian Li

Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures

Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon Kleinberg, Aryo Lotfi, Maithra Raghu, Chiyuan Zhang

Low-rank Optimal Transport: Approximation, Statistics and Debiasing

Meyer Scetbon, Marco Cuturi

MBW: Multi-view Bootstrapping in the Wild

Mosam Dabhi, Chaoyang Wang, Tim Clifford, László Jeni, Ian Fasel, Simon Lucey

Mean Estimation with User-level Privacy under Data Heterogeneity

Rachel Cummings, Vitaly Feldman, Audra McMillan, Kunal Talwar

Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss

Jason Altschuler, Kunal Talwar

Subspace Recovery from Heterogeneous Data with Non-isotropic Noise

John Duchi, Vitaly Feldman, Lunjia Hu, Kunal Talwar

Workshop Accepted Papers

Large-Scale Observational Study of the Causal Effects of a Behavioral Health Nudge

Achille Nazaret, Guillermo Sapiro

How Soft Labels Cause Divergence in Speech Recognition for Continuous Pseudo-Labeling

Tatiana Likhomanenko, Ronan Collobert, Navdeep Jaitly, Samy Bengio

Improving Generalization with Physical Equations

Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Joern-Henrik Jacobsen

Rewards Encoding Environment Dynamics Improves Preference-based Reinforcement Learning

Katherine Metcalf, Miguel Sarabia and Barry-John Theobald

Elastic Weight Consolidation Improves the Robustness of Self-Supervised Learning Methods under Transfer

Andrius Ovsianas, Jason Ramapuram, Dan Busbridge, Eeshan Gunesh Dhekane, Russ Webb

MAEEG: Masked Autoencoder for EEG Representation Learning

Sherry Chien, Hanlin Goh, Chris Sandino, Joseph Yitan Cheng

Homomorphic Self-Supervised Learning

Thomas Anderson Keller, Xavier Suau, Luca Zappella

Improving Generalization with Physical Equations

Antoine Wehenkel, Jens Behrmann, Guillermo Sapiro, Joern Jacobsen, Gilles Louppe, Hsiang (Shawn) Hsu

The Slingshot Mechanism: An Empirical Study of Adaptive Optimizers and the Grokking Phenomenon

Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Josh Susskind

Demos

RoomPlan

RoomPlan technology allows the user to captures a room and it's defining objects in a parametric format within minutes. Capture progress is automatically displayed and easy to understand at a glance. The resulting room capture is provided as a parametric representation of the room and can optionally be exported to USD, USDA or USDZ formats. The technology is supported on any of the Apple devices (iPad and iPhone) that are equipped with LiDAR sensor.

Information Intelligence

This demo aims to illustrate the rich information extraction and understanding capabilities embedded in select Apple products that use our state of the art search and intelligence technologies to cater to user’s information needs. These features leverage deep text and image understanding capabilities coupled with powerful search technologies to surface accurate and relevant information for user’s queries.

All NeurIPS attendees are invited to stop by the Apple booth (booth number 603, located in Hall G of the Ernest N. Morial Convention Center) to experience these demos in person.

Acknowledgements

Audra McMillan, Chong Wang, Congzheng Song, Devon Hjelm, Felix Bai, Hilal Asi, Jacob Yao, Jerome Bellegarda, Joe Futoma, Luca Zappella, Miguel Angel Bautista Martin, Sachin Agarwal, Sachin Mehta, and Tatiana Likhomanenko are reviewers for this conference.

Marian Stewart Bartlett is the treasurer for this conference.

Samy Bengio is a senior area chair and board member for this conference.

Kunal Talwar and Laurent Dinh are area chairs for this conference.

Arno Blaas co-organized the I Can't Believe It's Not Better: Understanding Deep Learning Through Empirical Falsification workshop.

Luca Zappella is a member of the coordination team for the I Can't Believe It's Not Better: Understanding Deep Learning Through Empirical Falsification workshop.

Let's innovate together. Build amazing machine-learned experiences with Apple. Discover opportunities for researchers, students, and developers by visiting our Work with us page.

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