no code implementations • NeurIPS 2016 • Bowei Yan, Purnamrita Sarkar
Clustering is one of the most important unsupervised problems in machine learning and statistics.
1 code implementation • 10 Jul 2016 • Bowei Yan, Purnamrita Sarkar
In statistics, an emerging body of work has been focused on combining information from both the edges in the network and the node covariates to infer community memberships.
no code implementations • 23 Oct 2016 • Bowei Yan, Oluwasanmi Koyejo, Kai Zhong, Pradeep Ravikumar
The proposed framework is general, as it applies to both batch and online learning, and to both linear and non-linear models.
no code implementations • 23 May 2017 • Bowei Yan, Mingzhang Yin, Purnamrita Sarkar
In this paper, we study convergence properties of the gradient Expectation-Maximization algorithm \cite{lange1995gradient} for Gaussian Mixture Models for general number of clusters and mixing coefficients.
no code implementations • 24 May 2017 • Bowei Yan, Purnamrita Sarkar, Xiuyuan Cheng
Community detection is a fundamental unsupervised learning problem for unlabeled networks which has a broad range of applications.
no code implementations • NeurIPS 2017 • Bowei Yan, Mingzhang Yin, Purnamrita Sarkar
In this paper, we study convergence properties of the gradient variant of Expectation-Maximization algorithm~\cite{lange1995gradient} for Gaussian Mixture Models for arbitrary number of clusters and mixing coefficients.
no code implementations • ICML 2018 • Bowei Yan, Oluwasanmi Koyejo, Kai Zhong, Pradeep Ravikumar
Complex performance measures, beyond the popular measure of accuracy, are increasingly being used in the context of binary classification.
no code implementations • NeurIPS 2018 • Soumendu Sundar Mukherjee, Purnamrita Sarkar, Y. X. Rachel Wang, Bowei Yan
Variational approximation has been widely used in large-scale Bayesian inference recently, the simplest kind of which involves imposing a mean field assumption to approximate complicated latent structures.
no code implementations • 24 Aug 2019 • Xiaoyan Wang, Ran Li, Bowei Yan, Oluwasanmi Koyejo
We propose a framework for constructing and analyzing multiclass and multioutput classification metrics, i. e., involving multiple, possibly correlated multiclass labels.
1 code implementation • 11 Jun 2020 • Mingzhang Yin, Nhat Ho, Bowei Yan, Xiaoning Qian, Mingyuan Zhou
This paper proposes a novel optimization method to solve the exact L0-regularized regression problem, which is also known as the best subset selection.
Methodology