Regression
Efficient Symmetric Norm Regression via Linear Sketching
Zhao Song, Ruosong Wang, Lin Yang, Hongyang Zhang, Peilin Zhong
Neural Information Processing Systems http://nips.cc/
Scalable Hyperparameter Transfer Learning
Valerio Perrone, Rodolphe Jenatton, Matthias W. Seeger, Cedric Archambeau
In this work, we aim to warm-start BO in the context of hyperparameter optimization (HPO).
Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning
It also does not enjoy SNIS's inherent stability and boundedness.
Conformalized Quantile Regression
Yaniv Romano, Evan Patterson, Emmanuel Candes
Conformal prediction is atechnique for constructing prediction intervals that attainvalidcoverage infinite samples, without making distributional assumptions. Despite this appeal, existing conformal methods can be unnecessarily conservativebecause theyform intervals ofconstant orweakly varying length across the input space.