Search Results for author: Bowei Yan

Found 10 papers, 2 papers with code

Probabilistic Best Subset Selection via Gradient-Based Optimization

1 code implementation11 Jun 2020 Mingzhang Yin, Nhat Ho, Bowei Yan, Xiaoning Qian, Mingyuan Zhou

In high-dimensional statistics, variable selection is an optimization problem aiming to recover the latent sparse pattern from all possible covariate combinations.

Methodology

Consistent Classification with Generalized Metrics

no code implementations24 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.

Classification General Classification

Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues

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.

Bayesian Inference Community Detection

Binary Classification with Karmic, Threshold-Quasi-Concave Metrics

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.

Classification General Classification

Convergence of Gradient EM on Multi-component Mixture of Gaussians

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.

Learning Theory

Provable Estimation of the Number of Blocks in Block Models

no code implementations24 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.

Community Detection

Convergence Analysis of Gradient EM for Multi-component Gaussian Mixture

no code implementations23 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.

Learning Theory

Online Classification with Complex Metrics

no code implementations23 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.

Classification General Classification +1

Covariate Regularized Community Detection in Sparse Graphs

1 code implementation10 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.

Community Detection

On Robustness of Kernel Clustering

no code implementations NeurIPS 2016 Bowei Yan, Purnamrita Sarkar

Clustering is one of the most important unsupervised problems in machine learning and statistics.

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