activity
20152022
most citedDiversified Hidden Markov Models for Sequential Labeling

25 citations · 55 across the 17 of their papers we have counts for

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8 papers · 1 filter

stat.ML2018

Diverse Online Feature Selection

Chapman Siu, Richard Yi Da Xu

Online feature selection has been an active research area in recent years. We propose a novel diverse online feature selection method based on Determinantal Point Processes (DPP).…

stat.ML2016

The Dependent Random Measures with Independent Increments in Mixture Models

Cheng Luo, Richard Yi Da Xu, Yang Xiang

When observations are organized into groups where commonalties exist amongst them, the dependent random measures can be an ideal choice for modeling. One of the propositions of the…

stat.ML2016

Smoothed Hierarchical Dirichlet Process: A Non-Parametric Approach to Constraint Measures

Cheng Luo, Yang Xiang, Richard Yi Da Xu

Time-varying mixture densities occur in many scenarios, for example, the distributions of keywords that appear in publications may evolve from year to year, video frame features as…

stat.ML2016

Bayesian nonparametric image segmentation using a generalized Swendsen-Wang algorithm

Richard Yi Da Xu, Francois Caron, Arnaud Doucet

Unsupervised image segmentation aims at clustering the set of pixels of an image into spatially homogeneous regions. We introduce here a class of Bayesian nonparametric models to a…

stat.ML20151 cited

Dependent Indian Buffet Process-based Sparse Nonparametric Nonnegative Matrix Factorization

Junyu Xuan, Jie Lu, Guangquan Zhang +2

Nonnegative Matrix Factorization (NMF) aims to factorize a matrix into two optimized nonnegative matrices appropriate for the intended applications. The method has been widely used…

stat.ML2015

Nonparametric Relational Topic Models through Dependent Gamma Processes

Junyu Xuan, Jie Lu, Guangquan Zhang +2

Traditional Relational Topic Models provide a way to discover the hidden topics from a document network. Many theoretical and practical tasks, such as dimensional reduction, docume…