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Found 6 papers, 0 papers with code
Exponential Concentration for Mutual Information Estimation with Application to Forests
We prove a new exponential concentration inequality for a plug-in estimator of the Shannon mutual information.
Nonparametric Reduced Rank Regression
We propose an approach to multivariate nonparametric regression that generalizes reduced rank regression for linear models.
Graph-Valued Regression
In this paper, we propose a semiparametric method for estimating $G(x)$ that builds a tree on the $X$ space just as in CART (classification and regression trees), but at each leaf of the tree estimates a graph.
Nonparametric regression and classification with joint sparsity constraints
We propose new families of models and algorithms for high-dimensional nonparametric learning with joint sparsity constraints.
Compressed Regression
Recent research has studied the role of sparsity in high dimensional regression and signal reconstruction, establishing theoretical limits for recovering sparse models from sparse data.
A correlated topic model of Science
This limitation stems from the use of the Dirichlet distribution to model the variability among the topic proportions.
Applications
