48 citations · 60 across the 3 of their papers we have counts for
5 papers · 1 filter
Feature Selection via the Intervened Interpolative Decomposition and its Application in Diversifying Quantitative Strategies
Jun Lu, Joerg Osterrieder
In this paper, we propose a probabilistic model for computing an interpolative decomposition (ID) in which each column of the observed matrix has its own priority or importance, so…
A survey on Bayesian inference for Gaussian mixture model
Jun Lu
Clustering has become a core technology in machine learning, largely due to its application in the field of unsupervised learning, clustering, classification, and density estimatio…
Reducing over-clustering via the powered Chinese restaurant process
Jun Lu, Meng Li, David Dunson
Dirichlet process mixture (DPM) models tend to produce many small clusters regardless of whether they are needed to accurately characterize the data - this is particularly true for…
An Equivalence of Fully Connected Layer and Convolutional Layer
Wei Ma, Jun Lu
This article demonstrates that convolutional operation can be converted to matrix multiplication, which has the same calculation way with fully connected layer. The article is help…
Hyperprior on symmetric Dirichlet distribution
Jun Lu
In this article we introduce how to put vague hyperprior on Dirichlet distribution, and we update the parameter of it by adaptive rejection sampling (ARS). Finally we analyze this…