NeurIPS 2023 Poster Session 4 (Thursday Morning)
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- čas přidán 25. 12. 2023
- OUTLINE:
0:30 - Activity Grammars for Temporal Action Segmentation
8:50 - Diffusion-TTA: Test-time Adaptation of Discriminative Models via Generative Feedback
17:05 - On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences
21:20 - Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming
27:10 - Equivariant Adaptation of Large Pretrained Models
33:10 - Multi-Head Adapter Routing for Cross-Task Generalization
39:25 - Geometry-Aware Adaptation for Pretrained Models
46:10 - Adversarial Learning for Feature Shift Detection and Correction
Papers:
Title: Activity Grammars for Temporal Action Segmentation
Link: arxiv.org/abs/2312.04266
Author:
Dayoung Gong, Joonseok Lee,
Deunsol Jung, Suha Kwak, Minsu Cho
--------
Title: Diffusion-TTA: Test-time Adaptation of Discriminative Models via Generative Feedback
Link: arxiv.org/abs/2311.16102
Author:
Mihir Prabhudesai, Tsung-Wei Ke,
Alexander C. Li, Deepak Pathak, Katerina Fragkiadaki
--------
Title: On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences
Link: arxiv.org/abs/2305.18423
Author:
Alireza Fathollah Pour, Hassan Ashtiani
--------
Title: Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming
Link: arxiv.org/abs/2310.19068
Author:
Gregory Dexter, Petros Drineas,
David P. Woodruff, Taisuke Yasuda
--------
Title: Equivariant Adaptation of Large Pretrained Models
Link: arxiv.org/pdf/2310.01647.pdf
Author:
Arnab Kumar Mondal, Siba Smarak Panigrahi,
Sékou-Oumar Kaba, Sai Rajeswar, Siamak Ravanbakhsh
--------
Title: Multi-Head Adapter Routing for Cross-Task Generalization
Link: arxiv.org/abs/2211.03831
Author:
Lucas Caccia, Edoardo Ponti, Zhan Su,
Matheus Pereira, Nicolas Le Roux, Alessandro Sordoni
--------
Title: Geometry-Aware Adaptation for Pretrained Models
Link: arxiv.org/abs/2307.12226
Author:
Nicholas Roberts, Xintong Li, Dyah Adila,
Sonia Cromp, Tzu-Heng Huang, Jitian Zhao, Frederic Sala
--------
Title: Adversarial Learning for Feature Shift Detection and Correction
Link: arxiv.org/abs/2312.04546
Author: Miriam Barrabes, Daniel Mas Montserrat,
Margarita Geleta, Xavier Giro-i-Nieto, Alexander G. Ioannidis
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OUTLINE:
0:30 - Activity Grammars for Temporal Action Segmentation
8:50 - Diffusion-TTA: Test-time Adaptation of Discriminative Models via Generative Feedback
17:05 - On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences
21:20 - Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming
27:10 - Equivariant Adaptation of Large Pretrained Models
33:10 - Multi-Head Adapter Routing for Cross-Task Generalization
39:25 - Geometry-Aware Adaptation for Pretrained Models
46:10 - Adversarial Learning for Feature Shift Detection and Correction
Thank you for a very good outline, and links to authors and papers! Awesome to learn about the engineers who are at the pointy end of the research.
She didn't recognize you at first because you weren't wearing sunglasses. I guess glasses really would work to disguise Superman.
Random ML guy? *puts on sunglasses* YANNIC THE ML GUY!?!?
cool, love this series.
Merry Christmas.
love this series
Really cool to see all the projects and people
wow! she is amazing! 👍👍👍
Thx again yannic🎉
울 작은 누나 멋있따🎉🎉🎉
Interesting! I am searching for NeurIPS contributions on the MAMBA architecture (S3 - Structured State Space Models) as an alternative for TRANSFORMERS for modeling really large sequences. Do you know where I can find those contributions?
Merry Christmas 🎄 and a good New Year !
Thank you! What about poster session 5?
They are speaking language of gods
Can I get the outro music link ?
Please cover quip#
야닉에 포스텍이라니!ㅋㅋ
Why the hate for MABs ? They're awesome !
great video u had to explain who u were cause the sunglasses were missing ;P just leave them out in ure normal videos too u look hreat without them
Yannic at NeurIPS:
What I see: czcams.com/video/qOrbrjBQf7Y/video.html