Search Results for author:
Found 7 papers, 2 papers with code
Hierarchical Methods of Moments
Spectral methods of moments provide a powerful tool for learning the parameters of latent variable models.
A New Spectral Method for Latent Variable Models
This paper presents an algorithm for the unsupervised learning of latent variable models from unlabeled sets of data.
Clustering Patients with Tensor Decomposition
In this paper we present a method for the unsupervised clustering of high-dimensional binary data, with a special focus on electronic healthcare records.
Generating Synthetic but Plausible Healthcare Record Datasets
Generating datasets that "look like" given real ones is an interesting tasks for healthcare applications of ML and many other fields of science and engineering.
Ranker-agnostic Contextual Position Bias Estimation
This paper introduces a method for modeling the probability of an item being seen in different contexts, e. g., for different users, with a single estimator.
Low-variance estimation in the Plackett-Luce model via quasi-Monte Carlo sampling
When adopting the PL model as a ranking policy, both tasks require the computation of expectations with respect to the model.
Fair Effect Attribution in Parallel Online Experiments
We suggest an approach to measure and disentangle the effect of simultaneous experiments by providing a cost sharing approach based on Shapley values.
