Deep Learning
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness
Fanny Yang, Zuowen Wang, Christina Heinze-Deml
Neural Information Processing Systems http://nips.cc/
MixMatch: A Holistic Approach to Semi-Supervised Learning
David Berthelot, Nicholas Carlini, Ian Goodfellow, Nicolas Papernot, Avital Oliver, Colin A. Raffel
Neural Information Processing Systems http://nips.cc/
Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences
In our work, we propose the first distributed method with client sampling and provable tolerance to Byzantine workers.
Rule Extrapolation in Language Models: A Study of Compositional Generalization on OOD Prompts Anna Mészáros
LLMs show remarkable emergent abilities, such as inferring concepts from presumably out-of-distribution prompts, known as in-context learning.