1.6k citations · 4.2k across the 71 of their papers we have counts for
8 papers · 1 filter
On the proliferation of support vectors in high dimensions
Daniel Hsu, Vidya Muthukumar, Ji Xu
The support vector machine (SVM) is a well-established classification method whose name refers to the particular training examples, called support vectors, that determine the maxim…
Statistical Query Lower Bounds for Tensor PCA
Rishabh Dudeja, Daniel Hsu
In the Tensor PCA problem introduced by Richard and Montanari (2014), one is given a dataset consisting of samples of i.i.d. Gaussian tensors of order wi…
On the number of variables to use in principal component regression
Ji Xu, Daniel Hsu
We study least squares linear regression over uncorrelated Gaussian features that are selected in order of decreasing variance. When the number of selected features is at m…
Consistent Risk Estimation in Moderately High-Dimensional Linear Regression
Ji Xu, Arian Maleki, Kamiar Rahnama Rad +1
Risk estimation is at the core of many learning systems. The importance of this problem has motivated researchers to propose different schemes, such as cross validation, generalize…
Mixing time estimation in reversible Markov chains from a single sample path
Daniel Hsu, Aryeh Kontorovich, David A. Levin +2
The spectral gap of a finite, ergodic, and reversible Markov chain is an important parameter measuring the asymptotic rate of convergence. In applications, the transition matri…
Parameter identification in Markov chain choice models
Arushi Gupta, Daniel Hsu
This work studies the parameter identification problem for the Markov chain choice model of Blanchet, Gallego, and Goyal used in assortment planning. In this model, the product sel…