119 citations · 207 across the 15 of their papers we have counts for
5 papers · 1 filter
Kernel Machines With Missing Responses
Tiantian Liu, Yair Goldberg
Missing responses is a missing data format in which outcomes are not always observed. In this work we develop kernel machines that can handle missing responses. First, we propose a…
Feature Elimination in Kernel Machines in moderately high dimensions
Sayan Dasgupta, Yair Goldberg, Michael Kosorok
We develop an approach for feature elimination in statistical learning with kernel machines, based on recursive elimination of features.We present theoretical properties of this me…
Support Vector Regression for Right Censored Data
Yair Goldberg, Michael R. Kosorok
We develop a unified approach for classification and regression support vector machines for data subject to right censoring. We provide finite sample bounds on the generalization e…
LLE with low-dimensional neighborhood representation
Yair Goldberg, Ya'acov Ritov
The local linear embedding algorithm (LLE) is a non-linear dimension-reducing technique, widely used due to its computational simplicity and intuitive approach. LLE first linearly…
Manifold Learning: The Price of Normalization
Y. Goldberg, A. Zakai, D. Kushnir +1
We analyze the performance of a class of manifold-learning algorithms that find their output by minimizing a quadratic form under some normalization constraints. This class consist…