Statistical Learning
62203a74e233e933b160711e791e1a02-Paper-Conference.pdf
Many PPS, such as Stan [1] or PyMC3 [2], limit the expressiveness of their language to ensure that the programs in their language always correspond tomodels with static support--i.e.
Uniform Convergence with Square-Root Lipschitz Loss
In linear regression, interpolating the square loss is equivalent to interpolating many other losses (such as the absolute loss) on the training set. Similarly, in the context of linear classification, many works (Soudry et al. 2018; Ji and Telgarsky 2019; Muthukumar et al. 2021) have shown that optimizing
A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm
Meta learning is a promising paradigm to enable skill transfer across tasks.
A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm Qi Wang
Meta learning is a promising paradigm to enable skill transfer across tasks.