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cs.LG2025
The Generative Leap: Sharp Sample Complexity for Efficiently Learning Gaussian Multi-Index Models
Alex Damian, Jason D. Lee, Joan Bruna
In this work we consider generic Gaussian Multi-index models, in which the labels only depend on the (Gaussian) -dimensional inputs through their projection onto a low-dimension…
cs.LG2025
Learning Compositional Functions with Transformers from Easy-to-Hard Data
Zixuan Wang, Eshaan Nichani, Alberto Bietti +4
Transformer-based language models have demonstrated impressive capabilities across a range of complex reasoning tasks. Prior theoretical work exploring the expressive power of tran…