Computing the Stationary Distribution Locally

no code implementations • NeurIPS 2013 • Christina E. Lee, Asuman Ozdaglar, Devavrat Shah

In this paper, we provide a novel algorithm that answers whether a chosen state in a MC has stationary probability larger than some $\Delta \in (0, 1)$.

Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering

no code implementations • NeurIPS 2016 • Dogyoon Song, Christina E. Lee, Yihua Li, Devavrat Shah

In contrast with classical regression, the features $x = (x_1(u), x_2(i))$ are not observed, making it challenging to apply standard regression methods to predict the unobserved ratings.

Collaborative Filtering Matrix Completion +2

Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation

no code implementations • NeurIPS 2017 • Christian Borgs, Jennifer Chayes, Christina E. Lee, Devavrat Shah

We show that the mean squared error (MSE) of our estimator converges to $0$ at the rate of $O(d^2 (pn)^{-2/5})$ as long as $\omega(d^5 n)$ random entries from a total of $n^2$ entries of $Y$ are observed (uniformly sampled), $\E[Y]$ has rank $d$, and the entries of $Y$ have bounded support.

Collaborative Filtering Community Detection +3