2023 International Conference on Machine Learning (ICML): Empowering Minds Through Cutting-Edge AI Advances
Introduction:
Apple is proud to sponsor the International Conference on Machine Learning (ICML) in Honolulu, Hawai’i from July 23 to 29. With over 6,000 attendees, ICML is dedicated to advancing artificial intelligence. Apple will be hosting various workshops and events throughout the conference, featuring industry experts and researchers. There will be poster presentations and oral presentations covering a wide range of topics, including view synthesis, optimal transport, structured representations, attention entropy collapse, and more. Additionally, there will be workshops on machine learning in healthcare, scientific and machine learning modeling, differentiable algorithms, logic reasoning, and privacy. Attendees can also experience live demos, such as browsing heat maps and generating 3D models using Object Capture. Don’t miss the opportunity to visit the Apple booth and engage with these exciting demonstrations. The conference also acknowledges the contributions of several individuals who have played key roles in organizing and reviewing the event.
Full Article: 2023 International Conference on Machine Learning (ICML): Empowering Minds Through Cutting-Edge AI Advances
Apple Sponsors International Conference on Machine Learning (ICML) in Honolulu, Hawai’i
Apple will be sponsoring the highly anticipated International Conference on Machine Learning (ICML) from July 23-29, in Honolulu, Hawai’i. ICML is a premier conference dedicated to advancing artificial intelligence and is expected to attract over 6,000 attendees. As part of their sponsorship, Apple will be hosting several workshops and events throughout the week. Here is a breakdown of the schedule:
Sunday, July 23
– Poster NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusion, presented by Jiatao Gu, Alex Trevithick, Kai-En Lin, Joshua M Susskind, Christian Theobalt, Lingjie Liu, Ravi Ramamoorthi
– Poster The Monge Gap: A Regularizer to Learn All Transport Maps, presented by Théo Uscidda, Marco Cuturi
– Poster DUET: 2D Structured and Approximately Equivariant Representations, presented by Xavi Suau, Federico Danieli, T. Anderson Keller, Arno Blaas, Chen Huang, Jason Ramapuram, Dan Busbridge, Luca Zappella
– Poster Stabilizing Transformer Training by Preventing Attention Entropy Collapse, presented by Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram, Yizhe Zhang, Jiatao Gu, Joshua M Susskind
– Poster Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps, presented by Marco Cuturi, Michal Klein, Pierre Ablin
– Oral Presentation Generalization on the Unseen, Logic Reasoning and Degree Curriculum, presented by Emmanuel Abbe, Samy Bengio, Aryo Lotfi, Kevin Rizk
Monday, July 24
– Poster UPSCALE: Unconstrained Channel Pruning, presented by Alvin Wan, Hanxiang Hao, Kaushik Patnaik, Yueyang Xu, Omer Hadad, David Güera, Zhile Ren, Qi Shan
– Poster Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime, presented by Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
– Poster Generalization on the Unseen, Logic Reasoning, and Degree Curriculum, presented by Emmanuel Abbe, Samy Bengio, Aryo Lotfi, Kevin Rizk
Tuesday, July 25
– Poster Robustness in Multimodal Learning under Train-Test Modality Mismatch, presented by Brandon McKinzie, Vaishaal Shankar, Joseph Cheng, Yinfei Yang, Jonathon Shlens, Alexander Toshev
– Poster The Role of Entropy and Reconstruction for Multi-View Self-Supervised Learning, presented by Borja Rodríguez Gálvez, Arno Blaas, Pau Rodriguez, Adam Golinski, Xavi Suau, Jason Ramapuram, Dan Busbridge, Luca Zappella
– Poster Federated Online and Bandit Convex Optimization, presented by Kumar Kshitij Patel, Lingxiao Wang, Aadirupa Saha, Nati Srebro
– Poster From Robustness to Privacy and Back, presented by Hilal Asi, Jonathan Ullman, Lydia Zakynthinou
– Social Event: Black in AI
Wednesday, July 26
– Workshop: Interpretable Machine Learning in Healthcare, co-organized by Agni Kumar
– Workshop: Synergy of Scientific and Machine Learning Modeling, co-organized by Jörn-Henrik Jacobsen and Antoine Wehenkel, with Andrew C. Miller as an invited speaker/panelist and Tatiana Likhomanenko as a reviewer
– Workshop: Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators, co-organized by Marco Cuturi
– Workshop: Knowledge and Logical Reasoning in the Era of Data-driven Learning, with Samy Bengio as an invited speaker
– Workshop: Women in Machine Learning, featuring a roundtable on mentorships hosted by Rishika Agarwal and Ivy Zhang
– Workshop: Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities, co-organized by Jianyu Wang, with Vojta Jina as an invited speaker
Friday, July 28
– Accepted Paper: Population Expansion for Training Language Models with Private Federated Learning, by Tatsuki Koga, Congzheng Song, Martin Pelikan, Mona Chitnis
– Accepted Paper: Differentially Private Heavy Hitters using Federated Analytics, by Karan Chadha, Junye Chen, John Duchi, Vitaly Feldman, Hanieh Hashemi, Omid Javidbakht, Audra McMillan, Kunal Talwar
Saturday, July 29
– Workshop: Indigenous in AI, a joint workshop with Queer in AI, co-organized by Sinead Williamson
In addition to these workshops and events, ICML attendees are also invited to visit the Apple booth (booth number 101, located in Hall III of the Hawai’i Convention Center) to experience two exciting demos. The first demo, called “Learning Iconic Scenes with Differential Privacy,” allows users to browse heat maps and histograms of popular locations and the photos taken at each location. The second demo, called “Object Capture,” allows users to generate high-quality 3D models from a series of photos, which can be viewed in AR Quick Look, integrated into Xcode projects, or used in professional 3D workflows.
ICML has a strong lineup of reviewers and chairs, including Samy Bengio, Ronan Collobert, Navdeep Jaitly, Marco Cuturi, Tatiana Likhomanenko, Rin Susa, Barry Theobald, Pau Rodriguez, Vimal Thilak, Pierre Ablin, Hilal Asi, Samira Abnar, Chen Huang, Vaishaal Shankar, Miguel Sarabia, Antoine Wehenkel, Agni Kumar, Bogdan Mazoure, Preetum Nakkiran, Rishika Agarwal, Yinfei Yang, Amir Shafiq, Jierui Lin, and Xavi Suau.
Overall, Apple’s sponsorship of the ICML conference and their participation in various workshops and events highlight their commitment to advancing the field of artificial intelligence and machine learning.
Summary: 2023 International Conference on Machine Learning (ICML): Empowering Minds Through Cutting-Edge AI Advances
Apple is sponsoring the International Conference on Machine Learning (ICML) in Honolulu, Hawai’i from July 23 to 29. The conference focuses on advancing artificial intelligence and is expected to have over 6,000 attendees. Apple will be hosting various workshops and events throughout the conference, including presentations on topics such as view synthesis, optimal transport, and transformer training. There will also be workshops on machine learning in healthcare, scientific and machine learning modeling, differentiable algorithms, logical reasoning, women in machine learning, and federated learning. Additionally, Apple will be showcasing demos of their research, including a demo on learning iconic scenes with privacy and object capture technology. Attendees can visit the Apple booth to experience these demos in person. Notable individuals involved in the conference include Samy Bengio, Ronan Collobert, Navdeep Jaitly, Sinead Williamson, and Marco Cuturi.
