4 papers · 1 filter
Universal rates of ERM for agnostic learning
Steve Hanneke, Mingyue Xu
The universal learning framework has been developed to obtain guarantees on the learning rates that hold for any fixed distribution, which can be much faster than the ones uniforml…
Universal Rates of Empirical Risk Minimization
Steve Hanneke, Mingyue Xu
The well-known empirical risk minimization (ERM) principle is the basis of many widely used machine learning algorithms, and plays an essential role in the classical PAC theory. A…
Efficient Estimation of the Central Mean Subspace via Smoothed Gradient Outer Products
Gan Yuan, Mingyue Xu, Samory Kpotufe +1
We consider the problem of sufficient dimension reduction (SDR) for multi-index models. The estimators of the central mean subspace in prior works either have slow (non-parametric)…
Distributed Semi-Supervised Sparse Statistical Inference
Jiyuan Tu, Weidong Liu, Xiaojun Mao +1
The debiased estimator is a crucial tool in statistical inference for high-dimensional model parameters. However, constructing such an estimator involves estimating the high-dimens…