🌟🌟New Workshop Alert 🌟🌟 Are you excited about new computing and learning paradigms for Human-Centric AI? Are you excited about doing it in a responsible manner? Join us at R2HCAI AAAI! more: r2hcai.github.io contact: [email protected] #AAAI2023

We aim to bring together researchers broadly interested in Representation Learning for Responsible Human-Centric AI to discuss recent and novel findings in the intersection of these communities. Speakers include Marzyeh Jacob Andreas Daniel Rueckert 𝙷𝚒𝚖𝚊 𝙻𝚊𝚔𝚔𝚊𝚛𝚊𝚓𝚞

Would you like to present your work at #AAAI2023? Working in the areas of Human-Centric AI/ResponsibleAI/Representation Learning? Consider submitting your work to the AAAI workshop on R2HCAI@AAAI2023. submission deadline: Nov. 8. more: r2hcai.github.io

Happy to share the news that Kathy Meier-Hellstern from Google will join R2HCAI@AAAI2023 as an invited speaker. follow us for more updates! more: r2hcai.github.io

Are you running a little late for R2HCAI@AAAI2023 submission? Don't worry! We have extended the submission deadline till Nov 14. Please follow us for more updates. website: r2hcai.github.io

Very well put!

🎉 Excited to announce that our paper has been ACCEPTED as a Spotlight Paper NeurIPS Conference! Interested to know how video self-supervised learning (VSSL) methods behave under different types of real-world distribution shifts (e.g., in OOD)? w/ Ahmad Beirami Ali Etemad #NeurIPS2023

Super excited to announce the Human-Centric Representation Learning workshop at #AAAI2024! Our workshop will bring together people working on generalizable models that take into account the unique properties of human-centric data. 📅 Deadline: 24/11 🔗 hcrl-workshop.github.io/2024/

🎉 Thrilled to announce that our paper, UnMixMatch, has been accepted at #AAAI24! UnMixMatch is a semi-supervised learning framework that can learn effective representations from unconstrained unlabelled data to scale up performance. W/ Ali Etemad arxiv.org/abs/2306.01222

We will never forgive and we will never forget!

🎉 Thrilled to announce that our paper, CoPrompt, has been accepted at #ICLR24 ICLR 2026. In this work, we propose Consistency-guided Prompt learning (CoPrompt), a new fine-tuning method that reduces the overfitting problem and improves generalization.

Last chance to submit your abstract. You will have a bit more time to submit the full paper.

I will be presenting our work Consistency-guided Prompt Learning (CoPrompt) at #ICLR today. If you are interested in the vision-language model, check out our poster at Halle B #240. Paper: arxiv.org/abs/2306.01195 Code: github.com/ShuvenduRoy/Co…

My hosts and collaborators: Sayna Ebrahimi Ali Etemad Ahmad Beirami Sercan Arık Tomas Pfister paper: arxiv.org/abs/2405.18654 blog: research.google/blog/halva-hal… code and models are coming soon, stay tuned.

Many people are in the middle of the #CVPR2025 deadline. So I'm sharing my guide to writing a CVPR paper (or any paper). My students have had this for years but I haven't shared it publicly before. I hope you find it useful and write a great paper. #CVPR2025 medium.com/@black_51980/w…

Segment, Shuffle, and Stitch Ali Etemad