6 citations · 8 across the 10 of their papers we have counts for
4 papers · 1 filter
Robust Mixture Learning when Outliers Overwhelm Small Groups
Daniil Dmitriev, Rares-Darius Buhai, Stefan Tiegel +5
We study the problem of estimating the means of well-separated mixtures when an adversary may add arbitrary outliers. While strong guarantees are available when the outlier fractio…
Computational-Statistical Gaps for Improper Learning in Sparse Linear Regression
Rares-Darius Buhai, Jingqiu Ding, Stefan Tiegel
We study computational-statistical gaps for improper learning in sparse linear regression. More specifically, given samples from a -sparse linear model in dimension , we…
Beyond Parallel Pancakes: Quasi-Polynomial Time Guarantees for Non-Spherical Gaussian Mixtures
Rares-Darius Buhai, David Steurer
We consider mixtures of Gaussian components with unknown means and unknown covariance (identical for all components) that are well-separated, i.e., distinct components ha…
Learning Restricted Boltzmann Machines with Sparse Latent Variables
Guy Bresler, Rares-Darius Buhai
Restricted Boltzmann Machines (RBMs) are a common family of undirected graphical models with latent variables. An RBM is described by a bipartite graph, with all observed variables…