NeurIPS 2023 Poster Session 4 - Highlights in Machine Learning Research

Explore cutting-edge machine learning research in this 58-minute video covering eight papers from NeurIPS 2023. Dive into topics like temporal action segmentation using activity grammars, test-time adaptation of discriminative models with diffusion, noise effects on recurrent neural network learning, sketching algorithms for sparse dictionary learning, equivariant adaptation of large pretrained models, multi-head adapter routing for cross-task generalization, geometry-aware model adaptation, and adversarial learning for feature shift detection and correction. Gain insights into the latest advancements in AI and deep learning from top researchers in the field.

- Activity Grammars for Temporal Action Segmentation
- Diffusion-TTA: Test-time Adaptation of Discriminative Models via Generative Feedback
- On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences
- Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming
- Equivariant Adaptation of Large Pretrained Models
- Multi-Head Adapter Routing for Cross-Task Generalization
- Geometry-Aware Adaptation for Pretrained Models
- Adversarial Learning for Feature Shift Detection and Correction