2 citations · 4 across the 5 of their papers we have counts for
5 papers
Global convergence analysis of mixtures of Exponential densities
Rajita Chandak, Kathryn Dullerud
The theoretical foundations of the EM algorithm are often thought of in the context of Gaussian mixture models, However, the practical use cases of the EM algorithm span beyond Gau…
Fast convergence of a Federated Expectation-Maximization Algorithm
Zhixu Tao, Rajita Chandak, Sanjeev Kulkarni
Data heterogeneity has been a long-standing bottleneck in studying the convergence rates of Federated Learning algorithms. In order to better understand the issue of data heterogen…
Convergence Rates of Oblique Regression Trees for Flexible Function Libraries
Matias D. Cattaneo, Rajita Chandak, Jason M. Klusowski
We develop a theoretical framework for the analysis of oblique decision trees, where the splits at each decision node occur at linear combinations of the covariates (as opposed to…
lpcde: Estimation and Inference for Local Polynomial Conditional Density Estimators
Matias D. Cattaneo, Rajita Chandak, Michael Jansson +1
This paper discusses the R package lpcde, which stands for local polynomial conditional density estimation. It implements the kernel-based local polynomial smoothing methods introd…
Boundary Adaptive Local Polynomial Conditional Density Estimators
Matias D. Cattaneo, Rajita Chandak, Michael Jansson +1
We begin by introducing a class of conditional density estimators based on local polynomial techniques. The estimators are boundary adaptive and easy to implement. We then study th…